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skyones-0

Kimi Project Intelligence MCP

by skyones-0

Kimi Project Intelligence MCP (Kimi-PIMCP) v0.2.0 ๐Ÿš€

A Model Context Protocol (MCP) server for Kimi-CLI that provides semantic indexing, intelligent context retrieval, and dynamic skill selection for enhanced code assistance.

โœจ Features

Core Features

  • Semantic Indexing - Index projects using ML embeddings (sentence-transformers)

  • Intelligent Retrieval - Find relevant code with cosine similarity + MMR for diversity

  • Skill Routing - Automatically detect user intent and select optimal skills

  • Caveman Compression - Heuristic-based text compression for token optimization

  • MCP Protocol - Full compatibility with Kimi-CLI via stdio JSON-RPC

New in v0.2.0

  • Incremental Indexing - Only reindex changed files (10x faster reindexing)

  • Query Caching - LRU cache for frequently used queries

  • File Watcher - Auto-reindex when files change

  • Dependency Graph - Analyze import relationships between files

  • Git Integration - Index only modified files vs HEAD

  • Code Summarization - Auto-summarize code chunks

  • Similar Code Detection - Find duplicate/similar code blocks

  • REST API - HTTP API for external integrations

  • Web UI - Beautiful web interface for managing indexes

Related MCP server: CodeAlive MCP

๐Ÿ“ Architecture

kimi-pimcp/
โ”œโ”€โ”€ src/
โ”‚   โ”œโ”€โ”€ indexer.py           # Semantic indexing with embeddings (OPTIMIZED)
โ”‚   โ”œโ”€โ”€ retriever.py         # Context retrieval with MMR + caching
โ”‚   โ”œโ”€โ”€ compressor.py        # Caveman text compression with tiktoken
โ”‚   โ”œโ”€โ”€ server.py            # MCP stdio server (multi-project support)
โ”‚   โ”œโ”€โ”€ file_watcher.py      # File change monitoring
โ”‚   โ”œโ”€โ”€ dependency_graph.py  # Import/dependency analysis
โ”‚   โ”œโ”€โ”€ git_integration.py   # Git integration for incremental updates
โ”‚   โ”œโ”€โ”€ code_summarizer.py   # Code summarization and duplicate detection
โ”‚   โ”œโ”€โ”€ rest_api.py          # HTTP REST API
โ”‚   โ”œโ”€โ”€ web_ui.py            # Web interface
โ”‚   โ””โ”€โ”€ skills/
โ”‚       โ”œโ”€โ”€ base.py          # Base skill classes
โ”‚       โ”œโ”€โ”€ router.py        # Intent classification
โ”‚       โ””โ”€โ”€ prompts/         # System prompts
โ”œโ”€โ”€ data/datasets/           # Training datasets
โ”œโ”€โ”€ tests/                   # Unit tests
โ”œโ”€โ”€ notebooks/               # Validation notebooks
โ””โ”€โ”€ docs/                    # Documentation

๐Ÿš€ Installation

Linux/Mac

chmod +x install.sh
./install.sh

Windows

.\install.ps1

Manual Installation

# Clone the repository
git clone <repository-url>
cd kimi-pimcp

# Create virtual environment
python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

# Install dependencies
pip install -r requirements.txt

# Pre-download models
python -c "from sentence_transformers import SentenceTransformer; SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')"

๐Ÿ’ป Usage

Running the MCP Server

# Start the MCP server
python src/server.py

# Or use the installed command
kimi-pimcp

The server communicates via stdin/stdout using JSON-RPC 2.0 protocol.

Running the REST API

# Start the REST API server
python src/rest_api.py --host 0.0.0.0 --port 8000

# With auto-reload (development)
python src/rest_api.py --reload

The API will be available at http://localhost:8000

Running the Web UI

# Start the web UI server
python src/web_ui.py

Then open http://localhost:8080 in your browser.

๐Ÿ› ๏ธ Available Tools

Core Tools

1. Initialize Index

{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "initialize_index",
    "arguments": {
      "project_path": "/path/to/project",
      "force_reindex": false
    }
  }
}

2. Query Context

{
  "jsonrpc": "2.0",
  "id": 2,
  "method": "tools/call",
  "params": {
    "name": "query_context",
    "arguments": {
      "query": "authenticate user",
      "top_k": 5,
      "filter_ext": [".py", ".js"],
      "use_mmr": true
    }
  }
}

3. Select Skill

{
  "jsonrpc": "2.0",
  "id": 3,
  "method": "tools/call",
  "params": {
    "name": "select_skill",
    "arguments": {
      "query": "fix login bug"
    }
  }
}

4. Compress Output

{
  "jsonrpc": "2.0",
  "id": 4,
  "method": "tools/call",
  "params": {
    "name": "compress_output",
    "arguments": {
      "text": "Please help me fix this bug...",
      "level": "full"
    }
  }
}

New Tools in v0.2.0

5. Get Query History

{
  "jsonrpc": "2.0",
  "id": 5,
  "method": "tools/call",
  "params": {
    "name": "get_query_history",
    "arguments": {
      "limit": 10
    }
  }
}

6. Switch Project

{
  "jsonrpc": "2.0",
  "id": 6,
  "method": "tools/call",
  "params": {
    "name": "switch_project",
    "arguments": {
      "project_path": "/path/to/other/project"
    }
  }
}

7. Get Dependencies

{
  "jsonrpc": "2.0",
  "id": 7,
  "method": "tools/call",
  "params": {
    "name": "get_dependencies",
    "arguments": {
      "filepath": "/path/to/file.py"
    }
  }
}

8. Find Similar Code

{
  "jsonrpc": "2.0",
  "id": 8,
  "method": "tools/call",
  "params": {
    "name": "find_similar_code",
    "arguments": {
      "filepath": "/path/to/file.py"
    }
  }
}

9. Summarize Chunk

{
  "jsonrpc": "2.0",
  "id": 9,
  "method": "tools/call",
  "params": {
    "name": "summarize_chunk",
    "arguments": {
      "content": "def hello(): print('world')",
      "chunk_type": "function",
      "language": "python"
    }
  }
}

10. Export/Import Index

{
  "jsonrpc": "2.0",
  "id": 10,
  "method": "tools/call",
  "params": {
    "name": "export_index",
    "arguments": {
      "output_path": "/path/to/export"
    }
  }
}

๐ŸŽฏ Skills

Skill

Description

Use Cases

debugger

Debug code issues

Errors, exceptions, crashes

architect

System design

Architecture, patterns, scalability

explainer

Explain code/concepts

Documentation, understanding

tester

Testing & QA

Unit tests, integration tests

caveman

Concise responses

Token-optimized output

โš™๏ธ Configuration

Edit config.yaml to customize:

models:
  embedding_model: "sentence-transformers/all-MiniLM-L6-v2"
  use_cross_encoder: true

indexer:
  supported_extensions: [".py", ".js", ".ts"]
  exclude_dirs: ["node_modules", ".git"]
  max_file_size_mb: 10

compressor:
  default_level: "auto"

performance:
  query_cache_size: 100
  model_cache_size: 2

๐Ÿ“Š Performance Targets

Operation

Target

v0.1.0

v0.2.0

Indexing

<100ms/file

~50ms

~30ms (incremental)

Query

<200ms

~100ms

~50ms (cached)

Classification

<10ms

~5ms

~3ms

Compression

<5ms

~2ms

~1ms

Memory

<500MB

~300MB

~250MB

๐Ÿงช Testing

# Run unit tests
python -m pytest tests/ -v

# Run with coverage
python -m pytest tests/ --cov=src --cov-report=html

# Run validation notebook
jupyter notebook notebooks/validation.ipynb

๐Ÿ“š REST API Endpoints

Endpoint

Method

Description

/health

GET

Health check

/index

POST

Index a project

/index/status

GET

Get indexing status

/query

POST

Search code

/compress

POST

Compress text

/skills/select

POST

Detect skill

/skills

GET

List skills

/stats

GET

Get all stats

/dependencies

GET

Get file dependencies

/dependencies/stats

GET

Dependency graph stats

/git/status

GET

Git status

/git/changes

GET

Git changes

/cache/clear

POST

Clear all caches

๐Ÿ“– API Reference

Indexer Module

from indexer import ProjectIndexer, get_indexer

indexer = get_indexer(project_path="/path/to/project")
stats = indexer.index_project("/path/to/project")
print(f"Indexed {stats['files_indexed']} files")
print(f"Skipped {stats['files_skipped']} unchanged files")

Retriever Module

from retriever import ContextRetriever, get_retriever

retriever = get_retriever()
retriever.load_index("/path/to/project")
results = retriever.query("authenticate user", top_k=5)

# Check cache stats
print(retriever.get_stats()['cache'])

File Watcher

from file_watcher import ProjectFileWatcher

def on_change(event):
    print(f"File {event.change_type.value}: {event.filepath}")

watcher = ProjectFileWatcher("/path/to/project", on_change)
watcher.start()

Dependency Graph

from dependency_graph import DependencyGraph

graph = DependencyGraph("/path/to/project")
graph.build()

# Get dependencies
deps = graph.get_dependencies("/path/to/file.py")
dependents = graph.get_dependents("/path/to/file.py")

# Find circular dependencies
cycles = graph.find_circular_dependencies()

Git Integration

from git_integration import GitIntegration

git = GitIntegration("/path/to/project")

# Get changed files since last commit
changes = git.get_changed_files_since("HEAD~1")
files_to_index, files_to_remove = git.get_files_to_index("HEAD~1")

๐Ÿค Contributing

  1. Fork the repository

  2. Create a feature branch (git checkout -b feature/amazing-feature)

  3. Make your changes

  4. Add tests

  5. Submit a pull request

๐Ÿ“„ License

MIT License - see LICENSE file for details.

๐Ÿ™ Acknowledgments

F
license - not found
-
quality - not tested
C
maintenance

Maintenance

โ€“Maintainers
โ€“Response time
โ€“Release cycle
โ€“Releases (12mo)
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