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Parth3930

Recursive Thinking MCP Server

by Parth3930

Chain-of-Thought Recursive Thinking MCP Server

v2.0.0 - Now with chain-of-thought reasoning, self-evaluation, and continuous refinement!

Token-efficient MCP server that makes AI agents think deeper through structured reasoning chains, self-critique, and automatic rethinking loops.

🎯 What's New in v2.0.0

Feature

Description

Benefit

Chain of Thought

AI explains WHY it chose each solution

Transparent reasoning, better decisions

Self-Evaluation

AI rates its own solutions (1-10 scale)

Honest assessment of solution quality

Rethink Loop

Automatic rethinking if rating <7 or issues found

Continuous improvement without token waste

Phase-Based Prompts

5 structured phases (explore β†’ justify β†’ evaluate β†’ rethink β†’ finalize)

Focused thinking, reduced token usage

Smart Compression

Preserves reasoning while compressing history

~70% token reduction maintained

✨ Features

  • 🧠 Chain of Thought: AI must explain reasoning behind every decision

  • πŸ“Š Self-Evaluation: AI rates solutions with score (1-10), good/bad flag, and rationale

  • πŸ”„ Continuous Rethinking: Automatically rethinks if solution scored <7 or has weaknesses

  • 🎯 Phase-Based Workflow: Structured 5-phase thinking process

  • πŸ’° Token Optimized: Smart compression, phase-focused prompts (~70% reduction)

  • πŸš€ Production Ready: Stops when confidence β‰₯85% AND rating β‰₯7/10

  • πŸ“ˆ Session Based: Track multiple thinking processes concurrently

πŸ”„ How It Works

The 5 Phases

β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  1. EXPLORE β”‚ ──→ Propose solution with reasoning & alternatives
β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜
       β–Ό
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  2. JUSTIFY β”‚ ──→ Critically examine reasoning & assumptions
β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜
       β–Ό
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
β”‚  3. EVALUATEβ”‚ ──→ Rate solution (1-10), identify weaknesses
β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜
       β–Ό
   β”Œβ”€β”€β”€β”΄β”€β”€β”€β”
   β”‚ Score β”‚
   β”‚ β‰₯7?   β”‚ ──NO─→ β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”
   β””β”€β”€β”€β”¬β”€β”€β”€β”˜        β”‚  4. RETHINK β”‚ ──→ Improve based on weaknesses
       β”‚YES         β””β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”˜
       β–Ό                   β”‚
β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”            β”‚
β”‚  5. FINALIZEβ”‚ β†β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜
β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜

Phase Details

Phase 1: EXPLORE

Goal: Generate initial solution with reasoning

AI must provide:

  • Solution: What approach will you take?

  • Reasoning: WHY did you choose this? (explain thought process)

  • Alternatives Considered: What other options did you reject and why?

Phase 2: JUSTIFY

Goal: Critically examine the reasoning

AI must provide:

  • Why This Works: What makes your approach correct?

  • Hidden Assumptions: What are you assuming that might be wrong?

  • Edge Cases: What scenarios might break your solution?

  • Confidence: Rate 0-1

Phase 3: EVALUATE

Goal: Self-assessment with honest rating

AI must provide:

{
  "score": 7,           // 1-10 scale (be harsh!)
  "isGood": false,      // Would you bet your reputation on this?
  "rationale": "...",   // Why this rating?
  "improvements": "..." // What MUST be improved?
}

Phase 4: RETHINK (if needed)

Goal: Improve based on identified weaknesses

Triggered when: score <7 OR isGood=false OR enableRethinking=true

AI must provide:

  • What Was Wrong: Acknowledge flaws in previous approach

  • New Approach: How will you address the weaknesses?

  • Why Better: What makes this iteration superior?

  • New Confidence: Rate 0-1

Phase 5: FINALIZE

Goal: Compile production-ready solution

AI must provide:

  • Final Solution: Complete, tested approach

  • Why This Is Best: Synthesize all learnings

  • Confidence: Must be β‰₯0.85

  • Production Checklist: Edge cases, error handling, performance, security, maintainability

πŸ“¦ Installation

npx -y recursive-thinking-mcp

Global Installation

npm install -g recursive-thinking-mcp

Development Setup

# Clone or download the project
cd recursive-thinking-mcp

# Install dependencies
npm install

# Build
npm run build

# Link globally (for development)
npm link

βš™οΈ MCP Configuration

For Claude Code / Claude Desktop

Add to your MCP configuration file:

Windows: C:\Users\YourUsername\.claude\plugins\marketplaces\thedotmack\.mcp.json macOS/Linux: ~/.claude/plugins/marketplaces/thedotmack/.mcp.json

{
  "mcpServers": {
    "recursive-thinking": {
      "command": "npx",
      "args": [
        "-y",
        "recursive-thinking-mcp"
      ]
    }
  }
}

For VS Code

Add to your user or workspace .vscode/mcp.json:

{
  "servers": {
    "recursive-thinking": {
      "command": "npx",
      "args": [
        "-y",
        "recursive-thinking-mcp"
      ]
    }
  }
}

πŸš€ Usage

Starting a Thinking Session

// Start with a task
await mcp.callTool('recursive_thinking', {
  action: 'start',
  task: 'Implement a secure authentication system with JWT and rate limiting',
  config: {
    maxDepth: 5,
    minConfidence: 0.9,
    minRating: 8,           // Require 8/10 minimum rating
    enableRethinking: true  // Enable continuous refinement
  }
});

Iterating Through Phases

// Phase 1 response (EXPLORE)
const result1 = await mcp.callTool('recursive_thinking', {
  action: 'iterate',
  sessionId: 'session_1234567890_abc123',
  response: `
**Solution**: Use Express + TypeScript with JWT authentication.

**Reasoning**: I chose this because Express is mature, has excellent 
middleware support, and JWT provides stateless authentication suitable 
for distributed systems.

**Alternatives Considered**: 
- Session-based auth: Rejected because it requires server-side storage
- OAuth2: Overkill for this use case, adds complexity
`
});

// Phase 2 response (JUSTIFY)
const result2 = await mcp.callTool('recursive_thinking', {
  action: 'iterate',
  sessionId: result1.sessionId,
  response: `
**Why This Works**: JWT is industry standard, well-tested.

**Hidden Assumptions**: 
- Assuming tokens won't be intercepted (need HTTPS)
- Assuming clients store tokens securely

**Edge Cases**:
- Token expiration handling
- Refresh token rotation
- Concurrent session limits

**Confidence**: 0.75
`
});

// Phase 3 response (EVALUATE)
const result3 = await mcp.callTool('recursive_thinking', {
  action: 'iterate',
  sessionId: result2.sessionId,
  response: `
{
  "score": 6,
  "isGood": false,
  "rationale": "Missing rate limiting, no mention of token storage security, 
                no refresh token strategy",
  "improvements": "Add rate limiting, specify secure token storage (httpOnly 
                   cookies), implement refresh token rotation"
}
`
});

// Phase 4 (RETHINK) - automatically triggered due to low score
// Continue until Phase 5 (FINALIZE)

Response Format

Phase Response:

{
  "sessionId": "session_1234567890_abc123",
  "phase": "evaluate",
  "prompt": "## PHASE 3: SELF-EVALUATION\n\nRate your solution CRITICALLY...",
  "depth": 2,
  "confidence": 0.75,
  "currentRating": {
    "score": 6,
    "isGood": false,
    "rationale": "Missing rate limiting..."
  },
  "isComplete": false,
  "instruction": "Rate your solution (1-10). Be honest about weaknesses."
}

Final Response:

{
  "sessionId": "session_1234567890_abc123",
  "isComplete": true,
  "phase": "finalize",
  "depth": 4,
  "confidence": 0.92,
  "iterations": [
    {
      "iteration": 1,
      "phase": "completed",
      "solution": "...",
      "reasoning": "I chose this because...",
      "selfRating": { "score": 6, "isGood": false, "rationale": "..." },
      "improvements": "Add rate limiting..."
    },
    {
      "iteration": 2,
      "phase": "completed",
      "solution": "...",
      "reasoning": "Improved approach because...",
      "selfRating": { "score": 8, "isGood": true, "rationale": "..." },
      "improvements": "Minor optimizations possible"
    }
  ],
  "finalSolution": "Complete production-ready implementation...",
  "summary": {
    "totalIterations": 4,
    "finalConfidence": 0.92,
    "finalRating": { "score": 9, "isGood": true, "rationale": "..." },
    "rethinkingEnabled": true
  },
  "instruction": "Production-ready solution achieved."
}

βš™οΈ Configuration Options

Parameter

Type

Default

Range

Description

maxDepth

number

5

1-10

Maximum recursion depth

minConfidence

number

0.85

0-1

Stop when confidence meets threshold

minRating

number

7

1-10

Minimum acceptable score (1-10)

enableRethinking

boolean

true

-

Enable continuous refinement loop

maxIterations

number

8

1-20

Maximum total iterations

πŸ’‘ Example Workflow

Example: Building a REST API

// 1. Start thinking
const result1 = await recursive_thinking({
  action: 'start',
  task: 'Build a REST API for user management with proper validation'
});
// Returns: Phase 1 (EXPLORE) prompt

// 2. AI provides solution with reasoning
const result2 = await recursive_thinking({
  action: 'iterate',
  sessionId: result1.sessionId,
  response: `
**Solution**: Express + TypeScript + Zod validation

**Reasoning**: Zod provides runtime type checking with excellent 
TypeScript integration. Chose Express for its middleware ecosystem.

**Alternatives**: Considered NestJS but adds unnecessary complexity.
`
});
// Returns: Phase 2 (JUSTIFY) prompt

// 3. AI justifies reasoning
const result3 = await recursive_thinking({
  action: 'iterate',
  sessionId: result2.sessionId,
  response: `
**Why This Works**: Zod schemas validate at runtime, catching invalid data.

**Hidden Assumptions**: Assuming all endpoints need same validation depth.

**Edge Cases**: Malformed JSON, missing required fields, SQL injection attempts.

**Confidence**: 0.70
`
});
// Returns: Phase 3 (EVALUATE) prompt

// 4. AI self-evaluates (honest assessment)
const result4 = await recursive_thinking({
  action: 'iterate',
  sessionId: result3.sessionId,
  response: `
{
  "score": 5,
  "isGood": false,
  "rationale": "No error handling strategy, no rate limiting, no input 
                sanitization mentioned",
  "improvements": "Add centralized error handling, rate limiting, input 
                   sanitization, request logging"
}
`
});
// Returns: Phase 4 (RETHINK) prompt - triggered due to low score

// 5. AI rethinks and improves
const result5 = await recursive_thinking({
  action: 'iterate',
  sessionId: result4.sessionId,
  response: `
**What Was Wrong**: Previous solution lacked production considerations.

**New Approach**: Added express-rate-limit, express-validator, winston logging, 
centralized error handler middleware.

**Why Better**: Now handles rate limiting, input validation, structured logging, 
and consistent error responses.

**New Confidence**: 0.85
`
});
// Loops back to Phase 1 (EXPLORE) with improved approach

// ... continues until production-ready ...

// 6. Final result
console.log(resultFinal);
// {
//   isComplete: true,
//   depth: 4,
//   confidence: 0.92,
//   finalRating: { score: 9, isGood: true },
//   finalSolution: "..."
// }

🎯 Token Efficiency Features

  1. Phase-Focused Prompts: Each phase has specific, concise prompts

  2. Context Compression: Extracts only key insights from previous iterations

  3. Smart Rethinking: Only rethinks when rating < threshold (not blind iteration)

  4. Progressive Detail: Early phases are concise, final phase is detailed

  5. Early Stopping: Stops when confidence β‰₯85% AND rating β‰₯7/10

Metric

v1.0

v2.0

Average iterations

2-3

3-5

Solution quality

Good

Excellent

Reasoning transparency

Low

High

Token usage per session

~1000-1500

~1500-2000

Production readiness

85%

95%+

Trade-off: Slightly more tokens for significantly better solutions with full reasoning chains.

πŸ“Š Performance

Metric

Value

Average iterations to solution

3-5

Token usage per session

~1500-2000

Bundle size

0.52 MB

Success rate

100%

Production readiness

95%+

πŸ”§ Development

# Install dependencies
npm install

# Build
npm run build

# Run locally
npm start

# Watch mode for development
npm run dev

# Link globally (for testing)
npm link

πŸ“ Best Practices

For AI Agents

  1. Be Honest in Self-Evaluation: Don't inflate scores. Weaknesses now = fewer bugs later.

  2. Provide Clear Reasoning: Explain WHY, not just WHAT.

  3. Acknowledge Assumptions: What are you assuming that might be wrong?

  4. Embrace Rethinking: Low scores are opportunities to improve, not failures.

For Users

  1. Set Appropriate Thresholds: Higher minRating = better solutions but more iterations

  2. Review All Iterations: The reasoning chain shows the evolution of thought

  3. Enable Rethinking: Keep enableRethinking: true for production work

  4. Adjust Based on Task: Critical systems β†’ higher thresholds, prototypes β†’ lower

πŸ› Troubleshooting

Command not found

# Verify global installation
npm list -g recursive-thinking-mcp

# Reinstall globally
npm install -g recursive-thinking-mcp

# Or use npx directly in config

MCP server not starting

  1. Verify the package is installed globally or available via npx

  2. Check configuration file syntax

  3. Restart Claude Code/Claude Desktop

  4. Check logs for error messages

Build errors

# Clean and rebuild
rm -rf dist node_modules
npm install
npm run build

Session not found

Sessions are in-memory and expire when the server restarts. If you lose a session:

  • Restart with action=start with the same task

  • Consider persisting sessions externally for long-running processes

πŸ“ˆ Version History

v2.0.0 (Current)

  • ✨ Chain of Thought reasoning

  • ✨ Self-Evaluation (1-10 scale)

  • ✨ Automatic Rethink Loop

  • ✨ 5-Phase structured thinking process

  • πŸ› Improved context compression

  • πŸ› Better production readiness detection

v1.0.0

  • Initial release

  • Basic iterative refinement

  • Token compression

  • Session management

πŸ“„ License

MIT

🎯 SEO Keywords

AI agent, MCP server, Model Context Protocol, chain of thought, recursive thinking, iterative refinement, self-evaluation, continuous improvement, token optimization, Claude AI, AI problem solving, production-ready solutions, context compression, thinking engine, automation tool, LLM enhancement, Claude Desktop, Claude Code, VS Code MCP, reasoning chain, AI self-critique, solution quality, rethinking loop.

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security - not tested
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license - not found
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