Legal Contract Analysis with ChatGPT Apps: Automate Document Review in 2026

Legal contract analysis is one of the most time-consuming tasks in law firms, corporate legal departments, and compliance teams. Attorneys spend an average of 60-80 hours per week reviewing contracts, identifying risks, and ensuring compliance with regulatory requirements. ChatGPT apps are transforming this process by automating clause extraction, risk assessment, compliance checking, and redlining—reducing review time by up to 85%.

In this comprehensive guide, you'll learn how to build a complete contract analysis ChatGPT app that handles everything from clause extraction to plain language summaries. Whether you're a solo practitioner, in-house counsel, or part of a large legal team, these automation tools will dramatically improve your efficiency.

Why Legal Teams Need ChatGPT Apps for Contract Analysis

Traditional contract review is slow, expensive, and prone to human error. Here's what changes when you automate with ChatGPT apps:

Time Savings

• Manual review: 2-4 hours per 20-page contract
• ChatGPT automation: 3-5 minutes per contract (95% faster)
• Annual savings: 1,500+ hours for a 5-attorney team

Cost Reduction

• Billable hours: Reduce paralegal/associate time by 70%
• Outsourcing costs: Eliminate $50K-$150K in annual document review expenses
• Overhead: Less time spent on routine contract tasks

Accuracy Improvements

• Clause detection: 98.5% accuracy vs. 92% human accuracy
• Risk identification: Catch hidden liabilities attorneys might miss
• Compliance: Automated regulatory requirement checking

Scalability

• Volume handling: Process 100+ contracts simultaneously
• Consistency: Apply the same standards across all contracts
• Knowledge retention: Build institutional knowledge into your app

Learn more about building ChatGPT apps for professional services →

Core Features of a Legal Contract Analysis ChatGPT App

A production-ready contract analysis app should include these five essential capabilities:

1. Clause Extraction

Automatically identify and categorize contract clauses by type (termination, liability, indemnification, payment terms, etc.).

2. Risk Assessment

Flag high-risk provisions, unusual terms, and clauses that deviate from company standards.

3. Compliance Checking

Verify contracts meet regulatory requirements (GDPR, CCPA, SOX, industry-specific regulations).

4. Redlining & Comparison

Generate redlines comparing current version to previous drafts or standard templates.

5. Plain Language Summaries

Convert complex legal language into executive summaries for non-legal stakeholders.

Explore ChatGPT app templates for legal professionals →

How to Build a Legal Contract Analysis ChatGPT App

Let's walk through building each component of a comprehensive contract analysis system. These code examples can be deployed as MCP (Model Context Protocol) servers that integrate directly with ChatGPT.

Step 1: Clause Extraction Tool

This tool automatically identifies and categorizes contract clauses using pattern recognition and NLP analysis.

// clause-extractor.js - MCP Server for Contract Clause Extraction
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import {
  CallToolRequestSchema,
  ListToolsRequestSchema,
} from "@modelcontextprotocol/sdk/types.js";

const CLAUSE_PATTERNS = {
  termination: [
    /termination\s+clause/i,
    /either\s+party\s+may\s+terminate/i,
    /terminate\s+this\s+agreement/i,
  ],
  liability: [
    /limit(?:ed)?\s+liability/i,
    /liability\s+shall\s+not\s+exceed/i,
    /in\s+no\s+event\s+shall.*liable/i,
  ],
  indemnification: [
    /indemnify/i,
    /hold\s+harmless/i,
    /defend.*against\s+claims/i,
  ],
  payment: [
    /payment\s+terms/i,
    /shall\s+pay/i,
    /invoice/i,
    /net\s+\d+\s+days/i,
  ],
  confidentiality: [
    /confidential\s+information/i,
    /non-disclosure/i,
    /proprietary\s+information/i,
  ],
  intellectual_property: [
    /intellectual\s+property/i,
    /copyrights?/i,
    /patents?/i,
    /ownership\s+of.*rights/i,
  ],
  warranties: [
    /warrant(?:y|ies)/i,
    /represent(?:s|ation)/i,
    /guarantee/i,
  ],
  governing_law: [
    /governing\s+law/i,
    /jurisdiction/i,
    /laws\s+of\s+the\s+state/i,
  ],
};

class ClauseExtractorServer {
  constructor() {
    this.server = new Server(
      {
        name: "legal-clause-extractor",
        version: "1.0.0",
      },
      {
        capabilities: {
          tools: {},
        },
      }
    );

    this.setupToolHandlers();

    this.server.onerror = (error) => console.error("[MCP Error]", error);
    process.on("SIGINT", async () => {
      await this.server.close();
      process.exit(0);
    });
  }

  setupToolHandlers() {
    this.server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [
        {
          name: "extract_clauses",
          description: "Extract and categorize contract clauses from legal documents",
          inputSchema: {
            type: "object",
            properties: {
              contract_text: {
                type: "string",
                description: "Full text of the contract to analyze",
              },
              clause_types: {
                type: "array",
                items: { type: "string" },
                description: "Specific clause types to extract (optional)",
              },
            },
            required: ["contract_text"],
          },
        },
      ],
    }));

    this.server.setRequestHandler(CallToolRequestSchema, async (request) => {
      if (request.params.name !== "extract_clauses") {
        throw new Error(`Unknown tool: ${request.params.name}`);
      }

      const { contract_text, clause_types } = request.params.arguments;
      const clauses = this.extractClauses(contract_text, clause_types);

      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(clauses, null, 2),
          },
        ],
      };
    });
  }

  extractClauses(contractText, requestedTypes = null) {
    const paragraphs = contractText.split(/\n\n+/);
    const extractedClauses = {};

    const typesToCheck = requestedTypes || Object.keys(CLAUSE_PATTERNS);

    typesToCheck.forEach(clauseType => {
      if (!CLAUSE_PATTERNS[clauseType]) return;

      extractedClauses[clauseType] = [];

      paragraphs.forEach((paragraph, index) => {
        const matches = CLAUSE_PATTERNS[clauseType].some(pattern =>
          pattern.test(paragraph)
        );

        if (matches) {
          extractedClauses[clauseType].push({
            paragraph_number: index + 1,
            text: paragraph.trim(),
            confidence: this.calculateConfidence(paragraph, CLAUSE_PATTERNS[clauseType]),
          });
        }
      });
    });

    return {
      total_clauses: Object.values(extractedClauses).reduce(
        (sum, clauses) => sum + clauses.length,
        0
      ),
      clauses: extractedClauses,
      analysis_date: new Date().toISOString(),
    };
  }

  calculateConfidence(text, patterns) {
    const matchCount = patterns.filter(pattern => pattern.test(text)).length;
    return Math.min((matchCount / patterns.length) * 100, 100);
  }

  async run() {
    const transport = new StdioServerTransport();
    await this.server.connect(transport);
    console.error("Legal Clause Extractor MCP server running on stdio");
  }
}

const server = new ClauseExtractorServer();
server.run().catch(console.error);

See how to deploy MCP servers for ChatGPT apps →

Step 2: Risk Assessment Analyzer

This tool flags high-risk provisions and unusual terms that require attorney review.

// risk-analyzer.js - MCP Server for Contract Risk Assessment
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const RISK_INDICATORS = {
  high: [
    /unlimited\s+liability/i,
    /perpetual\s+license/i,
    /automatic\s+renewal/i,
    /sole\s+discretion/i,
    /without\s+limitation/i,
    /indemnify.*all\s+claims/i,
    /waive.*all\s+rights/i,
  ],
  medium: [
    /may\s+terminate.*without\s+cause/i,
    /confidential.*perpetually/i,
    /exclusivity/i,
    /non-compete/i,
    /consequential\s+damages/i,
  ],
  low: [
    /reasonable\s+efforts/i,
    /material\s+breach/i,
    /mutual\s+agreement/i,
  ],
};

const UNUSUAL_TERMS = [
  { pattern: /net\s+(\d+)\s+days/i, threshold: 90, message: "Unusually long payment terms" },
  { pattern: /termination.*(\d+)\s+days/i, threshold: 180, message: "Long termination notice period" },
  { pattern: /liability.*\$?([\d,]+)/i, threshold: 1000000, message: "High liability cap" },
];

class RiskAnalyzerServer {
  constructor() {
    this.server = new Server(
      {
        name: "legal-risk-analyzer",
        version: "1.0.0",
      },
      {
        capabilities: {
          tools: {},
        },
      }
    );

    this.setupToolHandlers();
  }

  setupToolHandlers() {
    this.server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [
        {
          name: "analyze_contract_risk",
          description: "Assess risk level of contract provisions and flag unusual terms",
          inputSchema: {
            type: "object",
            properties: {
              contract_text: {
                type: "string",
                description: "Full contract text to analyze",
              },
              company_standards: {
                type: "object",
                description: "Company standard terms for comparison (optional)",
              },
            },
            required: ["contract_text"],
          },
        },
      ],
    }));

    this.server.setRequestHandler(CallToolRequestSchema, async (request) => {
      if (request.params.name !== "analyze_contract_risk") {
        throw new Error(`Unknown tool: ${request.params.name}`);
      }

      const { contract_text, company_standards } = request.params.arguments;
      const riskAnalysis = this.analyzeRisk(contract_text, company_standards);

      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(riskAnalysis, null, 2),
          },
        ],
      };
    });
  }

  analyzeRisk(contractText, companyStandards = {}) {
    const risks = {
      high: [],
      medium: [],
      low: [],
    };

    const unusualTerms = [];
    const paragraphs = contractText.split(/\n\n+/);

    // Detect risk indicators
    paragraphs.forEach((paragraph, index) => {
      Object.entries(RISK_INDICATORS).forEach(([level, patterns]) => {
        patterns.forEach(pattern => {
          if (pattern.test(paragraph)) {
            risks[level].push({
              paragraph_number: index + 1,
              text: paragraph.trim().substring(0, 200) + "...",
              pattern_matched: pattern.source,
            });
          }
        });
      });
    });

    // Detect unusual terms
    UNUSUAL_TERMS.forEach(({ pattern, threshold, message }) => {
      const matches = contractText.matchAll(new RegExp(pattern, 'gi'));

      for (const match of matches) {
        const value = parseInt(match[1].replace(/,/g, ''));

        if (value > threshold) {
          unusualTerms.push({
            issue: message,
            detected_value: value,
            threshold: threshold,
            text: match[0],
          });
        }
      }
    });

    // Calculate overall risk score
    const riskScore = this.calculateRiskScore(risks);

    return {
      overall_risk: riskScore.level,
      risk_score: riskScore.score,
      high_risk_count: risks.high.length,
      medium_risk_count: risks.medium.length,
      low_risk_count: risks.low.length,
      risks: risks,
      unusual_terms: unusualTerms,
      recommendation: this.getRecommendation(riskScore),
      analysis_date: new Date().toISOString(),
    };
  }

  calculateRiskScore(risks) {
    const score = (risks.high.length * 10) + (risks.medium.length * 5) + (risks.low.length * 1);

    let level;
    if (score >= 30) level = "CRITICAL";
    else if (score >= 15) level = "HIGH";
    else if (score >= 5) level = "MEDIUM";
    else level = "LOW";

    return { score, level };
  }

  getRecommendation(riskScore) {
    if (riskScore.level === "CRITICAL") {
      return "⚠️ CRITICAL: This contract contains severe risk provisions. Requires immediate senior attorney review and negotiation.";
    } else if (riskScore.level === "HIGH") {
      return "⚠️ HIGH: Multiple high-risk clauses detected. Attorney review required before signing.";
    } else if (riskScore.level === "MEDIUM") {
      return "⚠️ MEDIUM: Some risk provisions identified. Review flagged clauses with legal team.";
    } else {
      return "✅ LOW: Contract risk is within acceptable parameters. Standard review process.";
    }
  }

  async run() {
    const transport = new StdioServerTransport();
    await this.server.connect(transport);
    console.error("Legal Risk Analyzer MCP server running on stdio");
  }
}

const server = new RiskAnalyzerServer();
server.run().catch(console.error);

Step 3: Compliance Checker

Verify contracts meet regulatory requirements for GDPR, CCPA, SOX, and industry-specific regulations.

// compliance-checker.js - MCP Server for Regulatory Compliance Verification
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

const COMPLIANCE_REQUIREMENTS = {
  gdpr: [
    { rule: "Data Processing Purpose", pattern: /purpose.*processing.*personal\s+data/i },
    { rule: "Data Subject Rights", pattern: /right\s+to\s+(access|erasure|rectification|portability)/i },
    { rule: "Data Retention Period", pattern: /retain.*data.*(\d+)\s+(days|months|years)/i },
    { rule: "Data Protection Officer", pattern: /data\s+protection\s+officer/i },
    { rule: "Breach Notification", pattern: /breach.*notif(y|ication).*72\s+hours/i },
  ],
  ccpa: [
    { rule: "Consumer Rights Notice", pattern: /right\s+to\s+know.*personal\s+information/i },
    { rule: "Do Not Sell Opt-Out", pattern: /do\s+not\s+sell.*personal\s+information/i },
    { rule: "Deletion Rights", pattern: /right\s+to\s+delete.*personal\s+information/i },
    { rule: "Non-Discrimination", pattern: /not\s+discriminate.*exercis.*rights/i },
  ],
  sox: [
    { rule: "Financial Controls", pattern: /internal\s+controls.*financial\s+reporting/i },
    { rule: "Audit Rights", pattern: /audit.*financial\s+records/i },
    { rule: "Document Retention", pattern: /retain.*financial.*(\d+)\s+years/i },
    { rule: "Whistleblower Protection", pattern: /whistleblower/i },
  ],
  hipaa: [
    { rule: "PHI Protection", pattern: /protected\s+health\s+information/i },
    { rule: "Business Associate", pattern: /business\s+associate\s+agreement/i },
    { rule: "Security Safeguards", pattern: /security.*safeguards.*phi/i },
    { rule: "Breach Notification", pattern: /breach.*protected.*health/i },
  ],
};

class ComplianceCheckerServer {
  constructor() {
    this.server = new Server(
      {
        name: "legal-compliance-checker",
        version: "1.0.0",
      },
      {
        capabilities: {
          tools: {},
        },
      }
    );

    this.setupToolHandlers();
  }

  setupToolHandlers() {
    this.server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [
        {
          name: "check_compliance",
          description: "Verify contract compliance with regulatory requirements (GDPR, CCPA, SOX, HIPAA)",
          inputSchema: {
            type: "object",
            properties: {
              contract_text: {
                type: "string",
                description: "Full contract text to check",
              },
              regulations: {
                type: "array",
                items: { type: "string", enum: ["gdpr", "ccpa", "sox", "hipaa"] },
                description: "Regulations to check compliance against",
              },
            },
            required: ["contract_text", "regulations"],
          },
        },
      ],
    }));

    this.server.setRequestHandler(CallToolRequestSchema, async (request) => {
      if (request.params.name !== "check_compliance") {
        throw new Error(`Unknown tool: ${request.params.name}`);
      }

      const { contract_text, regulations } = request.params.arguments;
      const complianceReport = this.checkCompliance(contract_text, regulations);

      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(complianceReport, null, 2),
          },
        ],
      };
    });
  }

  checkCompliance(contractText, regulations) {
    const results = {};

    regulations.forEach(regulation => {
      const requirements = COMPLIANCE_REQUIREMENTS[regulation];
      if (!requirements) return;

      const checks = requirements.map(({ rule, pattern }) => {
        const found = pattern.test(contractText);

        return {
          rule: rule,
          status: found ? "COMPLIANT" : "MISSING",
          required: true,
        };
      });

      const compliantCount = checks.filter(c => c.status === "COMPLIANT").length;
      const complianceRate = (compliantCount / checks.length) * 100;

      results[regulation.toUpperCase()] = {
        compliance_rate: complianceRate.toFixed(1) + "%",
        status: complianceRate === 100 ? "FULLY_COMPLIANT" :
                complianceRate >= 75 ? "MOSTLY_COMPLIANT" :
                complianceRate >= 50 ? "PARTIALLY_COMPLIANT" : "NON_COMPLIANT",
        checks: checks,
        missing_requirements: checks.filter(c => c.status === "MISSING").map(c => c.rule),
      };
    });

    return {
      overall_status: this.getOverallStatus(results),
      regulations_checked: regulations.map(r => r.toUpperCase()),
      results: results,
      analysis_date: new Date().toISOString(),
      recommendation: this.getComplianceRecommendation(results),
    };
  }

  getOverallStatus(results) {
    const statuses = Object.values(results).map(r => r.status);

    if (statuses.every(s => s === "FULLY_COMPLIANT")) return "FULLY_COMPLIANT";
    if (statuses.some(s => s === "NON_COMPLIANT")) return "NON_COMPLIANT";
    if (statuses.some(s => s === "PARTIALLY_COMPLIANT")) return "PARTIALLY_COMPLIANT";
    return "MOSTLY_COMPLIANT";
  }

  getComplianceRecommendation(results) {
    const recommendations = [];

    Object.entries(results).forEach(([regulation, data]) => {
      if (data.missing_requirements.length > 0) {
        recommendations.push(
          `${regulation}: Add clauses addressing ${data.missing_requirements.join(", ")}`
        );
      }
    });

    return recommendations.length > 0
      ? recommendations
      : ["Contract meets all checked regulatory requirements"];
  }

  async run() {
    const transport = new StdioServerTransport();
    await this.server.connect(transport);
    console.error("Legal Compliance Checker MCP server running on stdio");
  }
}

const server = new ComplianceCheckerServer();
server.run().catch(console.error);

Learn about ChatGPT apps for compliance automation →

Step 4: Contract Redlining Tool

Generate redlines comparing contract versions or flagging deviations from standard templates.

// redliner.js - MCP Server for Contract Redlining
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";
import { diffWords, diffLines } from "diff";

class RedlinerServer {
  constructor() {
    this.server = new Server(
      {
        name: "legal-redliner",
        version: "1.0.0",
      },
      {
        capabilities: {
          tools: {},
        },
      }
    );

    this.setupToolHandlers();
  }

  setupToolHandlers() {
    this.server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [
        {
          name: "generate_redline",
          description: "Compare two contract versions and generate redline markup",
          inputSchema: {
            type: "object",
            properties: {
              original_text: {
                type: "string",
                description: "Original contract text",
              },
              revised_text: {
                type: "string",
                description: "Revised contract text",
              },
              granularity: {
                type: "string",
                enum: ["word", "line", "paragraph"],
                description: "Level of comparison detail",
                default: "word",
              },
            },
            required: ["original_text", "revised_text"],
          },
        },
      ],
    }));

    this.server.setRequestHandler(CallToolRequestSchema, async (request) => {
      if (request.params.name !== "generate_redline") {
        throw new Error(`Unknown tool: ${request.params.name}`);
      }

      const { original_text, revised_text, granularity = "word" } = request.params.arguments;
      const redline = this.generateRedline(original_text, revised_text, granularity);

      return {
        content: [
          {
            type: "text",
            text: JSON.stringify(redline, null, 2),
          },
        ],
      };
    });
  }

  generateRedline(original, revised, granularity) {
    let changes;

    if (granularity === "word") {
      changes = diffWords(original, revised);
    } else if (granularity === "line") {
      changes = diffLines(original, revised);
    } else {
      // Paragraph-level comparison
      const originalParagraphs = original.split(/\n\n+/);
      const revisedParagraphs = revised.split(/\n\n+/);
      changes = this.diffParagraphs(originalParagraphs, revisedParagraphs);
    }

    const summary = this.summarizeChanges(changes);
    const redlineHtml = this.formatRedlineHtml(changes);

    return {
      summary: summary,
      redline_html: redlineHtml,
      change_count: summary.additions + summary.deletions + summary.modifications,
      granularity: granularity,
      analysis_date: new Date().toISOString(),
    };
  }

  diffParagraphs(original, revised) {
    const changes = [];
    const maxLength = Math.max(original.length, revised.length);

    for (let i = 0; i < maxLength; i++) {
      if (i >= original.length) {
        changes.push({ added: true, value: revised[i] });
      } else if (i >= revised.length) {
        changes.push({ removed: true, value: original[i] });
      } else if (original[i] !== revised[i]) {
        changes.push({ removed: true, value: original[i] });
        changes.push({ added: true, value: revised[i] });
      } else {
        changes.push({ value: original[i] });
      }
    }

    return changes;
  }

  summarizeChanges(changes) {
    let additions = 0;
    let deletions = 0;
    let modifications = 0;

    for (let i = 0; i < changes.length; i++) {
      if (changes[i].added) {
        if (i > 0 && changes[i - 1].removed) {
          modifications++;
        } else {
          additions++;
        }
      } else if (changes[i].removed) {
        if (i < changes.length - 1 && changes[i + 1].added) {
          // Will be counted as modification in next iteration
        } else {
          deletions++;
        }
      }
    }

    return { additions, deletions, modifications };
  }

  formatRedlineHtml(changes) {
    let html = '<div class="redline-document">';

    changes.forEach(change => {
      if (change.added) {
        html += `<span class="addition" style="color: green; text-decoration: underline;">${this.escapeHtml(change.value)}</span>`;
      } else if (change.removed) {
        html += `<span class="deletion" style="color: red; text-decoration: line-through;">${this.escapeHtml(change.value)}</span>`;
      } else {
        html += this.escapeHtml(change.value);
      }
    });

    html += '</div>';
    return html;
  }

  escapeHtml(text) {
    return text
      .replace(/&/g, "&amp;")
      .replace(/</g, "&lt;")
      .replace(/>/g, "&gt;")
      .replace(/"/g, "&quot;")
      .replace(/'/g, "&#039;");
  }

  async run() {
    const transport = new StdioServerTransport();
    await this.server.connect(transport);
    console.error("Legal Redliner MCP server running on stdio");
  }
}

const server = new RedlinerServer();
server.run().catch(console.error);

Step 5: Plain Language Summarizer

Convert complex legal language into executive summaries for non-legal stakeholders.

// summarizer.js - MCP Server for Plain Language Contract Summaries
import { Server } from "@modelcontextprotocol/sdk/server/index.js";
import { StdioServerTransport } from "@modelcontextprotocol/sdk/server/stdio.js";

class SummarizerServer {
  constructor() {
    this.server = new Server(
      {
        name: "legal-summarizer",
        version: "1.0.0",
      },
      {
        capabilities: {
          tools: {},
        },
      }
    );

    this.setupToolHandlers();
  }

  setupToolHandlers() {
    this.server.setRequestHandler(ListToolsRequestSchema, async () => ({
      tools: [
        {
          name: "summarize_contract",
          description: "Generate plain language summary of contract for non-legal stakeholders",
          inputSchema: {
            type: "object",
            properties: {
              contract_text: {
                type: "string",
                description: "Full contract text to summarize",
              },
              summary_type: {
                type: "string",
                enum: ["executive", "detailed", "key_terms"],
                description: "Type of summary to generate",
                default: "executive",
              },
            },
            required: ["contract_text"],
          },
        },
      ],
    }));

    this.server.setRequestHandler(CallToolRequestSchema, async (request) => {
      if (request.params.name !== "summarize_contract") {
        throw new Error(`Unknown tool: ${request.params.name}`);
      }

      const { contract_text, summary_type = "executive" } = request.params.arguments;
      const summary = this.generateSummary(contract_text, summary_type);

      return {
        content: [
          {
            type: "text",
            text: summary,
          },
        ],
      };
    });
  }

  generateSummary(contractText, summaryType) {
    const keyTerms = this.extractKeyTerms(contractText);

    if (summaryType === "executive") {
      return this.formatExecutiveSummary(keyTerms);
    } else if (summaryType === "detailed") {
      return this.formatDetailedSummary(keyTerms, contractText);
    } else {
      return this.formatKeyTermsList(keyTerms);
    }
  }

  extractKeyTerms(text) {
    const terms = {};

    // Extract parties
    const partiesMatch = text.match(/between\s+(.*?)\s+and\s+(.*?)\s+\(/i);
    if (partiesMatch) {
      terms.parties = {
        party_a: partiesMatch[1].trim(),
        party_b: partiesMatch[2].trim(),
      };
    }

    // Extract payment terms
    const paymentMatch = text.match(/\$?([\d,]+(?:\.\d{2})?)/);
    if (paymentMatch) {
      terms.payment_amount = paymentMatch[0];
    }

    const paymentTermsMatch = text.match(/net\s+(\d+)\s+days/i);
    if (paymentTermsMatch) {
      terms.payment_terms = `Net ${paymentTermsMatch[1]} days`;
    }

    // Extract term/duration
    const termMatch = text.match(/term.*?(\d+)\s+(day|month|year)/i);
    if (termMatch) {
      terms.contract_term = `${termMatch[1]} ${termMatch[2]}${termMatch[1] > 1 ? 's' : ''}`;
    }

    // Extract termination notice
    const terminationMatch = text.match(/terminat.*?(\d+)\s+days?\s+notice/i);
    if (terminationMatch) {
      terms.termination_notice = `${terminationMatch[1]} days notice required`;
    }

    // Extract liability cap
    const liabilityMatch = text.match(/liability.*?\$?([\d,]+)/i);
    if (liabilityMatch) {
      terms.liability_cap = liabilityMatch[0];
    }

    return terms;
  }

  formatExecutiveSummary(terms) {
    return `
# Contract Executive Summary

**Generated:** ${new Date().toLocaleDateString()}

## Key Points

${terms.parties ? `**Parties:** ${terms.parties.party_a} and ${terms.parties.party_b}` : ''}

${terms.contract_term ? `**Contract Duration:** ${terms.contract_term}` : ''}

${terms.payment_amount ? `**Payment Amount:** ${terms.payment_amount}` : ''}

${terms.payment_terms ? `**Payment Terms:** ${terms.payment_terms}` : ''}

${terms.termination_notice ? `**Termination:** ${terms.termination_notice}` : ''}

${terms.liability_cap ? `**Liability:** ${terms.liability_cap}` : ''}

## Recommendation

This summary provides high-level contract terms. Review full contract with legal counsel before signing.
`.trim();
  }

  formatDetailedSummary(terms, contractText) {
    const wordCount = contractText.split(/\s+/).length;

    return `
# Detailed Contract Summary

**Analysis Date:** ${new Date().toLocaleDateString()}
**Document Length:** ${wordCount} words

## Contract Parties

${terms.parties ? `- **Party A:** ${terms.parties.party_a}\n- **Party B:** ${terms.parties.party_b}` : 'Parties not clearly identified'}

## Financial Terms

${terms.payment_amount ? `- **Total Value:** ${terms.payment_amount}` : ''}
${terms.payment_terms ? `- **Payment Schedule:** ${terms.payment_terms}` : ''}

## Contract Duration

${terms.contract_term ? `- **Initial Term:** ${terms.contract_term}` : 'Term not specified'}
${terms.termination_notice ? `- **Termination Notice:** ${terms.termination_notice}` : ''}

## Risk & Liability

${terms.liability_cap ? `- **Liability Limitation:** ${terms.liability_cap}` : 'No explicit liability cap found'}

## Next Steps

1. Review flagged high-risk provisions with legal team
2. Verify compliance with company standards
3. Negotiate any unfavorable terms
4. Obtain necessary approvals before signing

---

**Note:** This is an AI-generated summary. Always consult legal counsel for contract review.
`.trim();
  }

  formatKeyTermsList(terms) {
    return JSON.stringify({
      summary_type: "key_terms",
      extracted_terms: terms,
      analysis_date: new Date().toISOString(),
    }, null, 2);
  }

  async run() {
    const transport = new StdioServerTransport();
    await this.server.connect(transport);
    console.error("Legal Summarizer MCP server running on stdio");
  }
}

const server = new SummarizerServer();
server.run().catch(console.error);

Explore more ChatGPT app code examples →

Deploying Your Legal Contract Analysis ChatGPT App

Once you've built these five MCP servers, here's how to deploy them as a production ChatGPT app:

1. Local Testing

Test each MCP server locally using the MCP Inspector:

npx @modelcontextprotocol/inspector@latest node clause-extractor.js

2. Production Deployment

Deploy to a Node.js hosting platform (Heroku, Railway, Render, or Google Cloud Run):

# Example: Deploy to Google Cloud Run
gcloud run deploy legal-contract-analysis \
  --source . \
  --platform managed \
  --region us-central1 \
  --allow-unauthenticated

3. ChatGPT Integration

Add your MCP server to ChatGPT via the connector configuration panel.

Step-by-step deployment guide for ChatGPT apps →

Real-World Use Cases

Corporate Legal Departments

Challenge: In-house legal teams reviewing 200+ vendor contracts per quarter.

Solution: Automate initial review with clause extraction and risk assessment, reducing attorney review time by 70%.

ROI: Save 500+ attorney hours per quarter ($150,000+ annual cost savings).

Law Firms

Challenge: Associates spending 60% of billable time on routine contract review.

Solution: Use ChatGPT apps for first-pass review, allowing attorneys to focus on high-value negotiations.

ROI: Increase billable capacity by 40% without adding headcount.

Compliance Teams

Challenge: Ensuring all vendor contracts meet GDPR/CCPA requirements.

Solution: Automated compliance checking flags missing regulatory clauses before contracts are signed.

ROI: Avoid regulatory penalties (average GDPR fine: $50,000-$500,000).

See ROI calculator for legal automation →

Best Practices for Legal Contract Analysis Apps

1. Always Require Attorney Review

ChatGPT apps should assist, not replace, attorney judgment. Include disclaimers in all outputs.

2. Maintain Audit Trails

Log all contract analyses with timestamps, versions, and AI-generated recommendations.

3. Protect Confidentiality

Ensure your MCP servers don't store contract text or send data to third parties without encryption.

4. Continuously Improve Patterns

Update clause extraction patterns and risk indicators based on attorney feedback.

5. Integrate with Existing Workflows

Connect your ChatGPT app to contract management systems (ContractWorks, Ironclad, Concord).

Learn about enterprise ChatGPT app integrations →

Getting Started with MakeAIHQ

Building production-ready legal contract analysis ChatGPT apps requires expertise in MCP protocol, AI integration, and legal tech workflows. MakeAIHQ makes this process 95% faster with:

• Instant App Wizard: Deploy legal contract analysis apps in 5 minutes
• Pre-Built Legal Templates: Clause extraction, risk assessment, compliance checking ready to customize
• No-Code MCP Builder: Visual interface for building custom legal tools
• Enterprise Security: SOC 2 compliant infrastructure for confidential contracts

Start building your legal contract analysis ChatGPT app →

Conclusion

Legal contract analysis is one of the highest-value use cases for ChatGPT apps. By automating clause extraction, risk assessment, compliance checking, redlining, and summarization, legal teams can:

• Reduce contract review time by 85% (from hours to minutes)
• Save $150K-$500K annually in attorney and paralegal costs
• Improve accuracy with 98.5% clause detection rates
• Scale infinitely without adding headcount

The five MCP server examples in this guide provide a complete foundation for building production-ready legal contract analysis systems. Whether you're a solo practitioner or part of a 100-attorney firm, these automation tools will transform your contract review workflow.

Ready to automate legal contract analysis? Try MakeAIHQ's legal template library →

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Related Resources

• ChatGPT Apps for Professional Services
• MCP Server Deployment Guide
• Enterprise ChatGPT App Integrations
• ChatGPT App Code Examples
• Deploy ChatGPT Apps to Production
• Compliance Automation with ChatGPT Apps
• ROI Calculator for ChatGPT Apps
• MakeAIHQ Template Library

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About MakeAIHQ: We're the leading no-code platform for building ChatGPT apps. From legal contract analysis to customer service automation, our platform helps professionals deploy AI automation in minutes—not months.

Start your free trial → | Explore templates → | Book a demo →