CodeWeaver

Semantic code search for Claude, Gemini, ChatGPT 鈥� across 166+ languages

Installation 鈥�
Features 鈥�
Comparison

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.

You, or Claude, or your intern, can ask questions like:

• "Where do we handle OAuth tokens?"
• "Find all API endpoint definitions"
• "Show me error handling in the payment flow"

CodeWeaver returns the exact functions, classes, and code blocks 鈥� even in unfamiliar languages or massive repositories.

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, actual understanding

鈿狅笍 Alpha Release: This works, but it's early. Use it, break it, help shape it.

How CodeWeaver Stacks Up

Quick Reference Matrix

Notes:

• Serena tool count: Varies by context (20+ in claude-code, up to 35 total available)
• Serena prompt overhead: Measured with 21 active tools in claude-code context (~16,000 tokens)
• Language counts: CodeWeaver supports 166+ unique languages (27 with AST parsing, 139 with intelligent delimiter-based chunking)

馃搳 [See detailed competitive analysis 鈫抅competitive_analysis

馃殌 Getting Started

Quick Install

Using the CLI with uv:

# Add CodeWeaver to your project
uv add --prerelease allow --dev code-weaver

# Initialize config and MCP setup
cw init

# Verify setup
cw doctor

# Start the server
cw server

馃摑 Note: cw init defaults to CodeWeaver's recommended profile:

• 馃攽 Voyage AI API key (generous free tier)
• 馃梽锔� Qdrant instance (cloud or local, both free options)

Want full offline? Use cw init --profile quickstart for local-only operation.

馃惓 Prefer Docker? [See Docker setup guide 鈫抅docker_guide

MCP Configuration

To watch and handle your files, CodeWeaver always runs an HTTP server. You can connect to that or use your typical stdio setup:

cw init adds CodeWeaver to your project's .mcp.json:

{
  "mcpServers": {
    "codeweaver": {
      "type": "stdio",
      "cmd": "uv",
      "args": ["run", "codeweaver", "server"],
      "env": {"VOYAGE_API_KEY": "your-key-here"}
    }
  }
}

or with http:

{
  "mcpServers": {
    "codeweaver": {
      "type": "http",
      "url": "http://127.0.0.1:9328"
    }
  }
}

鉁� Features

馃攳 Smart Search

• Hybrid search (sparse + dense vectors)
• AST-level understanding (27 languages)
• Semantic relationships
• Language-aware chunking (166+ languages)

馃寪 Language Support

• 27 languages with full AST/semantic parsing
• 166+ languages with language-aware chunking
• Cross-language normalization
• Family heuristics for smart fallback

馃攧 Resilient & Offline

• Full offline operation with local models
• Automatic failover to backup vector store
• Works airgapped (no cloud required)
• Graceful degradation with health monitoring

馃攲 Provider Flexibility

• 17 embedding providers
• 50+ embedding models
• Sparse & dense embedding model support
• 5 reranking providers
• [See full provider list 鈫抅providers_list

鈿欙笍 Configuration

• ~15 config sources (TOML/YAML/JSON/ENV)
• Cloud secret stores (AWS/Azure/GCP)
• Hierarchical merging
• Profiles for common setups

馃洜锔� Developer Experience

• Live indexing with file watching
• Move detection (no re-indexing duplicates)
• Full CLI (cw / codeweaver)
• Health & metrics endpoints

馃挱 Philosophy

The Bigger Picture

I started building CodeWeaver because I believe AI agents need better context infrastructure. Right now:

• Agents re-read the same huge files repeatedly
• They get shallow, text-based context instead of structural understanding
• They are mostly given tools built for humans, not for how they actually work
• You don't control what context they see or how they get it

CodeWeaver addresses this with one focused capability: structural + semantic code understanding that you control and can deploy however you want.

Is this solving a big problem? We think so. But we're in alpha; we're probably not there yet. We also need real-world usage to prove it. That's where you come in. Use it, make it better. Worst case -- it's a good tool, best case -- you get better results and cut costs on AI.

馃摉 [Read the detailed rationale 鈫抅why_codeweaver

Built with 鉂わ笍 by Knitli

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