Kimi Project Intelligence MCP
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Here is a step-by-step guide with screenshots.
Kimi Project Intelligence MCP (Kimi-PIMCP) v0.2.0 ๐
A Model Context Protocol (MCP) server for Kimi-CLI that provides semantic indexing, intelligent context retrieval, and dynamic skill selection for enhanced code assistance.
โจ 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
๐ Architecture
kimi-pimcp/
โโโ src/
โ โโโ indexer.py # Semantic indexing with embeddings (OPTIMIZED)
โ โโโ retriever.py # Context retrieval with MMR + caching
โ โโโ compressor.py # Caveman text compression with tiktoken
โ โโโ server.py # MCP stdio server (multi-project support)
โ โโโ file_watcher.py # File change monitoring
โ โโโ dependency_graph.py # Import/dependency analysis
โ โโโ git_integration.py # Git integration for incremental updates
โ โโโ code_summarizer.py # Code summarization and duplicate detection
โ โโโ rest_api.py # HTTP REST API
โ โโโ web_ui.py # Web interface
โ โโโ skills/
โ โโโ base.py # Base skill classes
โ โโโ router.py # Intent classification
โ โโโ prompts/ # System prompts
โโโ data/datasets/ # Training datasets
โโโ tests/ # Unit tests
โโโ notebooks/ # Validation notebooks
โโโ docs/ # Documentation๐ Installation
Linux/Mac
chmod +x install.sh
./install.shWindows
.\install.ps1Manual 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')"๐ป Usage
Running the MCP Server
# Start the MCP server
python src/server.py
# Or use the installed command
kimi-pimcpThe 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 --reloadThe API will be available at http://localhost:8000
Running the Web UI
# Start the web UI server
python src/web_ui.pyThen open http://localhost:8080 in your browser.
๐ ๏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"
}
}
}๐ฏ 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 |
โ๏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: 2๐ 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 |
๐งช 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.ipynb๐ REST API Endpoints
Endpoint | Method | Description |
| GET | Health check |
| POST | Index a project |
| GET | Get indexing status |
| POST | Search code |
| POST | Compress text |
| POST | Detect skill |
| GET | List skills |
| GET | Get all stats |
| GET | Get file dependencies |
| GET | Dependency graph stats |
| GET | Git status |
| GET | Git changes |
| POST | Clear all caches |
๐ 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")๐ค Contributing
Fork the repository
Create a feature branch (
git checkout -b feature/amazing-feature)Make your changes
Add tests
Submit a pull request
๐ License
MIT License - see LICENSE file for details.
๐ Acknowledgments
sentence-transformers for embeddings
FAISS for vector search
scikit-learn for classification
watchdog for file watching
FastAPI for REST API
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