MCP Server

Maintained

Apache-2.0

com.knitli/codeweaver MCP Server

com.knitli/codeweaver

Semantic code search for AI agents with hybrid AST-aware understanding across 166 languages.

What is the com.knitli/codeweaver MCP server?

CodeWeaver is a semantic code search MCP server that gives AI agents precise, structural context from codebases through hybrid search (semantic + AST + keyword). It supports 166+ languages with AST-level understanding for 27 of them, and reduces token usage by 60–80% compared to keyword-only search.

CodeWeaver provides industrial-grade code context infrastructure for AI agents like Claude. Instead of generic keyword grep results, it delivers exact structural matches through hybrid semantic search, AST awareness, and language-specific chunking. It's designed for reliability with automatic local fallback, works airgapped, and uses 100% dependency injection for extensibility.

How to install com.knitli/codeweaver

Copy-paste configuration for popular MCP clients.

transport: stdio

Config generated by PluginBench — verify against the source before use.

Environment / auth

CODEWEAVER_CONFIG_FILE
Specify a custom config file path for CodeWeaver. Only needed if not using the default locations.
CODEWEAVER_DEBUG
Enable debug mode for CodeWeaver.
CODEWEAVER_EMBEDDING_API_KEY
secret
Specify the API key for the embedding provider, if required. Note: {', '.join([p for p in _providers_for_kind('embedding') if p.])}
CODEWEAVER_EMBEDDING_MODEL
Specify the embedding model to use.
CODEWEAVER_EMBEDDING_PROVIDER
Specify the embedding provider to use.
CODEWEAVER_HOST
Set the server host for CodeWeaver.
CODEWEAVER_LOG_LEVEL
Set the log level for CodeWeaver (e.g., DEBUG, INFO, WARNING, ERROR).
CODEWEAVER_MCP_PORT
Set the MCP server port for CodeWeaver if using http transport for mcp. Not required if using the default port (9328), or stdio transport.
CODEWEAVER_PORT
Set the port for the codeweaver management server (information and management endpoints).
CODEWEAVER_PROFILE
Use a premade provider settings profile for CodeWeaver.
CODEWEAVER_PROJECT_NAME
Set the project name for CodeWeaver.
CODEWEAVER_PROJECT_PATH
Set the project path for CodeWeaver.
CODEWEAVER_RERANKING_API_KEY
secret
Specify the API key for the reranking provider, if required.
CODEWEAVER_RERANKING_MODEL
Specify the reranking model to use.
CODEWEAVER_RERANKING_PROVIDER
Specify the reranking provider to use.
CODEWEAVER_SPARSE_EMBEDDING_MODEL
Specify the sparse embedding model to use.
CODEWEAVER_SPARSE_EMBEDDING_PROVIDER
Specify the sparse embedding provider to use.
CODEWEAVER_VECTOR_STORE_API_KEY
secret
Specify the API key for the vector store, if required.
CODEWEAVER_VECTOR_STORE_PORT
Specify the port for the vector store.
CODEWEAVER_VECTOR_STORE_PROVIDER
Specify the vector store provider to use.
CODEWEAVER_VECTOR_STORE_URL
Specify the URL for the vector store.
CODEWEAVER__TELEMETRY__DISABLE_TELEMETRY
Disable telemetry data collection.
CODEWEAVER__TELEMETRY__TOOLS_OVER_PRIVACY
Opt-in to potentially identifying collection of query and search result data. This is invaluable for helping us improve CodeWeaver's search capabilities. If privacy is a higher priority, do not enable this setting.
HTTPS_PROXY
HTTP proxy for requests (Used by: Azure, Azure, Voyage)
OPENAI_API_KEY
secret
API key for OpenAI-compatible services (not necessarily an API key *for* OpenAI). The OpenAI client also requires an API key, even if you don't actually need one for your provider (like local Ollama). So provide a dummy key if needed. (Used by: Azure, Cerebras, Deepseek, Fireworks, Github, Groq, Heroku, Moonshot, Ollama, Openai, Openrouter, Perplexity, Together, Vercel, X Ai)
OPENAI_LOG
One of: 'debug', 'info', 'warning', 'error' (Used by: Azure, Cerebras, Deepseek, Fireworks, Github, Groq, Heroku, Moonshot, Ollama, Openai, Openrouter, Perplexity, Together, Vercel, X Ai)
SSL_CERT_FILE
Path to the SSL certificate file for requests (Used by: Azure, Azure, Voyage)
AI_GATEWAY_API_KEY
secret
API key for Vercel service
AWS_ACCOUNT_ID
AWS Account ID for Bedrock service
AWS_REGION
AWS region for Bedrock service
AWS_SECRET_ACCESS_KEY
secret
AWS Secret Access Key for Bedrock service
AZURE_COHERE_API_KEY
secret
API key for Azure Cohere service (cohere models on Azure)
AZURE_COHERE_ENDPOINT
Endpoint for Azure Cohere service (cohere models on Azure)
AZURE_COHERE_REGION
Region for Azure Cohere service
AZURE_OPENAI_API_KEY
secret
API key for Azure OpenAI service (OpenAI models on Azure)
AZURE_OPENAI_ENDPOINT
Endpoint for Azure OpenAI service (OpenAI models on Azure)
AZURE_OPENAI_REGION
Region for Azure OpenAI service (OpenAI models on Azure)
COHERE_API_KEY
Your Cohere API Key
CO_API_URL
Host URL for Cohere service
DEEPSEEK_API_KEY
secret
API key for DeepSeek service
GEMINI_API_KEY
Your Google Gemini API Key
GOOGLE_API_KEY
Your Google API Key
HF_HUB_VERBOSITY
Log level for Hugging Face Hub client
HF_TOKEN
API key/token for Hugging Face service
INFERENCE_KEY
secret
API key for Heroku service
INFERENCE_URL
Host URL for Heroku service
MISTRAL_API_KEY
Your Mistral API Key
QDRANT__LOG_LEVEL
Log level for Qdrant service
QDRANT__SERVICE__API_KEY
secret
API key for Qdrant service
QDRANT__SERVICE__ENABLE_TLS
Enable TLS for Qdrant service, expects truthy or false value (e.g. 1 for on, 0 for off).
QDRANT__SERVICE__HOST
Hostname of the Qdrant service; do not use for URLs with schemes (e.g. 'http://')
QDRANT__SERVICE__HTTP_PORT
Port number for the Qdrant service
QDRANT__TLS__CERT
Path to the TLS certificate file for Qdrant service. Only needed if using a self-signed certificate. If you're using qdrant-cloud, you don't need this.
TAVILY_API_KEY
Your Tavily API Key
TOGETHER_API_KEY
secret
API key for Together service
VERCEL_OIDC_TOKEN
secret
OIDC token for Vercel service
VOYAGE_API_KEY
secret
API key for Voyage service

~/Library/Application Support/Claude/claude_desktop_config.json

{
  "mcpServers": {
    "codeweaver": {
      "command": "uvx",
      "args": [
        "code-weaver",
        "server",
        "--project",
        "--config",
        "--host",
        "--port",
        "--transport",
        "--verbose",
        "--debug"
      ],
      "env": {
        "CODEWEAVER_CONFIG_FILE": "<YOUR_CODEWEAVER_CONFIG_FILE>",
        "CODEWEAVER_DEBUG": "<YOUR_CODEWEAVER_DEBUG>",
        "CODEWEAVER_EMBEDDING_API_KEY": "<YOUR_CODEWEAVER_EMBEDDING_API_KEY>",
        "CODEWEAVER_EMBEDDING_MODEL": "<YOUR_CODEWEAVER_EMBEDDING_MODEL>",
        "CODEWEAVER_EMBEDDING_PROVIDER": "<YOUR_CODEWEAVER_EMBEDDING_PROVIDER>",
        "CODEWEAVER_HOST": "<YOUR_CODEWEAVER_HOST>",
        "CODEWEAVER_LOG_LEVEL": "<YOUR_CODEWEAVER_LOG_LEVEL>",
        "CODEWEAVER_MCP_PORT": "<YOUR_CODEWEAVER_MCP_PORT>",
        "CODEWEAVER_PORT": "<YOUR_CODEWEAVER_PORT>",
        "CODEWEAVER_PROFILE": "<YOUR_CODEWEAVER_PROFILE>",
        "CODEWEAVER_PROJECT_NAME": "<YOUR_CODEWEAVER_PROJECT_NAME>",
        "CODEWEAVER_PROJECT_PATH": "<YOUR_CODEWEAVER_PROJECT_PATH>",
        "CODEWEAVER_RERANKING_API_KEY": "<YOUR_CODEWEAVER_RERANKING_API_KEY>",
        "CODEWEAVER_RERANKING_MODEL": "<YOUR_CODEWEAVER_RERANKING_MODEL>",
        "CODEWEAVER_RERANKING_PROVIDER": "<YOUR_CODEWEAVER_RERANKING_PROVIDER>",
        "CODEWEAVER_SPARSE_EMBEDDING_MODEL": "<YOUR_CODEWEAVER_SPARSE_EMBEDDING_MODEL>",
        "CODEWEAVER_SPARSE_EMBEDDING_PROVIDER": "<YOUR_CODEWEAVER_SPARSE_EMBEDDING_PROVIDER>",
        "CODEWEAVER_VECTOR_STORE_API_KEY": "<YOUR_CODEWEAVER_VECTOR_STORE_API_KEY>",
        "CODEWEAVER_VECTOR_STORE_PORT": "<YOUR_CODEWEAVER_VECTOR_STORE_PORT>",
        "CODEWEAVER_VECTOR_STORE_PROVIDER": "<YOUR_CODEWEAVER_VECTOR_STORE_PROVIDER>",
        "CODEWEAVER_VECTOR_STORE_URL": "<YOUR_CODEWEAVER_VECTOR_STORE_URL>",
        "CODEWEAVER__TELEMETRY__DISABLE_TELEMETRY": "<YOUR_CODEWEAVER_TELEMETRY_DISABLE_TELEMETRY>",
        "CODEWEAVER__TELEMETRY__TOOLS_OVER_PRIVACY": "<YOUR_CODEWEAVER_TELEMETRY_TOOLS_OVER_PRIVACY>",
        "HTTPS_PROXY": "<YOUR_HTTPS_PROXY>",
        "OPENAI_API_KEY": "<YOUR_OPENAI_API_KEY>",
        "OPENAI_LOG": "<YOUR_OPENAI_LOG>",
        "SSL_CERT_FILE": "<YOUR_SSL_CERT_FILE>",
        "AI_GATEWAY_API_KEY": "<YOUR_AI_GATEWAY_API_KEY>",
        "AWS_ACCOUNT_ID": "<YOUR_AWS_ACCOUNT_ID>",
        "AWS_REGION": "<YOUR_AWS_REGION>",
        "AWS_SECRET_ACCESS_KEY": "<YOUR_AWS_SECRET_ACCESS_KEY>",
        "AZURE_COHERE_API_KEY": "<YOUR_AZURE_COHERE_API_KEY>",
        "AZURE_COHERE_ENDPOINT": "<YOUR_AZURE_COHERE_ENDPOINT>",
        "AZURE_COHERE_REGION": "<YOUR_AZURE_COHERE_REGION>",
        "AZURE_OPENAI_API_KEY": "<YOUR_AZURE_OPENAI_API_KEY>",
        "AZURE_OPENAI_ENDPOINT": "<YOUR_AZURE_OPENAI_ENDPOINT>",
        "AZURE_OPENAI_REGION": "<YOUR_AZURE_OPENAI_REGION>",
        "COHERE_API_KEY": "<YOUR_COHERE_API_KEY>",
        "CO_API_URL": "<YOUR_CO_API_URL>",
        "DEEPSEEK_API_KEY": "<YOUR_DEEPSEEK_API_KEY>",
        "GEMINI_API_KEY": "<YOUR_GEMINI_API_KEY>",
        "GOOGLE_API_KEY": "<YOUR_GOOGLE_API_KEY>",
        "HF_HUB_VERBOSITY": "<YOUR_HF_HUB_VERBOSITY>",
        "HF_TOKEN": "<YOUR_HF_TOKEN>",
        "INFERENCE_KEY": "<YOUR_INFERENCE_KEY>",
        "INFERENCE_URL": "<YOUR_INFERENCE_URL>",
        "MISTRAL_API_KEY": "<YOUR_MISTRAL_API_KEY>",
        "QDRANT__LOG_LEVEL": "<YOUR_QDRANT_LOG_LEVEL>",
        "QDRANT__SERVICE__API_KEY": "<YOUR_QDRANT_SERVICE_API_KEY>",
        "QDRANT__SERVICE__ENABLE_TLS": "<YOUR_QDRANT_SERVICE_ENABLE_TLS>",
        "QDRANT__SERVICE__HOST": "<YOUR_QDRANT_SERVICE_HOST>",
        "QDRANT__SERVICE__HTTP_PORT": "<YOUR_QDRANT_SERVICE_HTTP_PORT>",
        "QDRANT__TLS__CERT": "<YOUR_QDRANT_TLS_CERT>",
        "TAVILY_API_KEY": "<YOUR_TAVILY_API_KEY>",
        "TOGETHER_API_KEY": "<YOUR_TOGETHER_API_KEY>",
        "VERCEL_OIDC_TOKEN": "<YOUR_VERCEL_OIDC_TOKEN>",
        "VOYAGE_API_KEY": "<YOUR_VOYAGE_API_KEY>"
      }
    }
  }
}

Tools & capabilities

Tools this server exposes to the agent.

find_code — Hybrid semantic and AST-aware code search across your codebase, supporting 166+ languages with precise structural understanding.

Use cases

Help Claude find the exact functions that validate OAuth tokens across your codebase without noise
Reduce token usage by 60–80% when providing code context to AI agents by returning only relevant structural matches
Search code semantically across 166+ languages with AST-level understanding for 27 languages
Set up a fully local, airgapped code search system with no cloud dependencies using FastEmbed and local Qdrant
Swap between embedding providers (Voyage AI, OpenAI, local FastEmbed) without code changes using dependency injection

com.knitli/codeweaver MCP server FAQ

What does CodeWeaver do?

CodeWeaver provides semantic code search for AI agents using hybrid search (semantic vectors + AST + keyword matching). It understands code structure across 166+ languages and returns precise context instead of noisy keyword results, reducing token usage by 60–80%.

Is CodeWeaver free?

CodeWeaver is open-source under MIT or Apache-2.0 license. The 'quickstart' profile uses only free, local tools (FastEmbed + Qdrant). The 'recommended' profile uses Voyage AI embeddings, which has a free tier.

How do I install CodeWeaver in Cursor or Claude?

Install via PyPI (`uv add code-weaver`), then run `cw init --profile quickstart` for local-only setup or `cw init --profile recommended` for higher precision. Start the daemon with `cw start`. It exposes an MCP server that Cursor and Claude can connect to.

Does CodeWeaver require authentication?

The 'quickstart' profile requires no authentication and runs fully local. The 'recommended' profile requires a Voyage AI API key (free tier available). You can also configure other embedding providers like OpenAI.

Is CodeWeaver still maintained?

CodeWeaver is no longer actively maintained by Knitli, but the code is open-source (MIT/Apache-2.0) and available for forking. It is well-tested and functional.

What languages does CodeWeaver support?

CodeWeaver supports 166+ languages for semantic search and language-aware chunking. AST-level structural understanding is available for 27 languages including Python, JavaScript, Java, Go, Rust, and others.

README (reference)

Source of truth, from the repository.

[!WARNING]

CodeWeaver is no longer maintained

We're really proud of CodeWeaver and think it's pretty awesome, but we can't maintain it anymore.

We're focused on something else.

CodeWeaver is (was?) a sophisticated, smart, code search tool with wide provider support. and it's still licensed under your choice of MIT or Apache-2.0.

So please, fork it and build something great!

CodeWeaver

Exquisite Context for Agents — Infrastructure that is Extensible, Predictable, and Resilient.

Documentation • Installation • Features • Comparison

</div>

What It Does

CodeWeaver gives Claude and other AI agents precise context from your codebase. Not keyword grep. Not whole-file dumps. Actual structural understanding through hybrid semantic search.

CodeWeaver is Professional Context Infrastructure. With 100% Dependency Injection (DI) and a Pydantic-driven configuration system, it provides the reliability and extensibility required for industrial-grade AI deployments.

Example:

Without CodeWeaver:
  Claude: "Let me search for 'auth'... here are 50 files mentioning authentication"
  Result: Generic code, wrong context, wasted tokens

With CodeWeaver:
  You: "Where do we validate OAuth tokens?"
  Claude gets: The exact 3 functions across 2 files, with surrounding context
  Result: Precise answers, focused context, 60-80% token reduction

CodeWeaver is no longer in alpha!

Early Release (0.x): CodeWeaver is in active development. APIs may change between minor versions. It's very well-tested but still in 'it works on my machine' territory. Use it, break it, help shape it.

How CodeWeaver Stacks Up

Quick Reference Matrix

Feature	CodeWeaver	Legacy Search Tools
Search Type	Hybrid (Semantic + AST + Keyword)	Keyword Only
Context Quality	Exquisite / High-Precision	Noisy / Irrelevant
Extensibility	DI-Driven (Zero-Code Provider Swap)	Hardcoded
Reliability	Resilient (Automatic Local Fallback)	Fails on API Timeout
Token Usage	Optimized (60–80% Reduction)	Wasted on Noise

🚀 Getting Started

Quick Install

Using the CLI with uv:

# Add CodeWeaver to your project
uv add code-weaver

# Initialize with a profile (recommended uses Voyage AI)
cw init --profile recommended

# Verify setup
cw doctor

# Start the background daemon
cw start

📝 Note: cw init supports different Profiles:

recommended: High-precision search (Voyage AI + Qdrant)

quickstart: 100% local, private, and free (FastEmbed + Local Qdrant)

Want full offline? See the Local-Only Guide.

🐳 Prefer Docker? See Docker setup guide →

✨ Features

🔍 Exquisite Context

Hybrid search (sparse + dense vectors)
AST-level understanding (27 languages)
Reciprocal Rank Fusion (RRF)
Language-aware chunking (166+ languages)

</td> <td width="50%">

🛡️ Industrial Resilience

Automatic local fallback (FastEmbed)
Circuit breaker pattern for APIs
Works airgapped (no cloud required)
Pydantic-driven validation at boot-time

</td> </tr> <tr> <td>

🧩 Universal Extensibility

100% DI-driven architecture
17+ integrated providers
Custom provider API
Zero-code provider swapping

</td> <td>

🛠️ Developer Experience

Live indexing with file watching
Diagnostic tool (cw doctor)
Multiple CLI aliases (cw / codeweaver)
Selectable profiles for easy setup

</td> </tr> </table>

💭 Philosophy: Context is Oxygen

AI agents face too much irrelevant context, causing token waste, missed patterns, and hallucinations. CodeWeaver addresses this with one focused capability: structural + semantic code understanding that you control.

Curation over Collection: Give agents exactly what they need, nothing more.
Privacy-First: Your code stays local if you want it to.
Infrastructure over Tooling: Built to be the reliable foundation for your AI stack.

📖 Read the detailed rationale →

Official Documentation: docs.knitli.com/codeweaver/

Built with ❤️ by Knitli

⬆ Back to top

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