MCP server for indexing and querying codebases using CocoIndex
Project description
light weight MCP for code that just works
A super light-weight, effective embedded MCP (AST-based) that understand and searches your codebase that just works! Using CocoIndex - an Rust-based ultra performant data transformation engine. No blackbox. Works for Claude, Codex, Cursor - any coding agent.
- Instant token saving by 70%.
- 1 min setup - Just claude/codex mcp add works!
🌟 Please help star CocoIndex if you like this project!
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Get Started - zero config, let's go!!
Using pipx:
pipx install cocoindex-code # first install
pipx upgrade cocoindex-code # upgrade
Using uv:
uv tool install --upgrade cocoindex-code --prerelease explicit --with "cocoindex>=1.0.0a24"
Claude
claude mcp add cocoindex-code -- cocoindex-code
Codex
codex mcp add cocoindex-code -- cocoindex-code
OpenCode
opencode mcp add
Enter MCP server name: cocoindex-code
Select MCP server type: local
Enter command to run: cocoindex-code
Or use opencode.json:
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"cocoindex-code": {
"type": "local",
"command": [
"cocoindex-code"
]
}
}
}
Build the Index
For large codebases, we recommend running the indexer once before using the MCP so you can see the progress:
cocoindex-code index
This lets you monitor the indexing process and ensure everything is ready. After the initial build, the MCP server will automatically keep the index up-to-date in the background as files change.
For small projects you can skip this step — the MCP server will build the index automatically on first use.
When Is the MCP Triggered?
Once configured, your coding agent (Claude Code, Codex, Cursor, etc.) automatically decides when semantic code search is helpful — especially for finding code by description, exploring unfamiliar codebases, fuzzy/conceptual matches, or locating implementations without knowing exact names.
You can also nudge the agent explicitly, e.g. "Use the cocoindex-code MCP to find how user sessions are managed." For persistent instructions, add guidance to your project's AGENTS.md or CLAUDE.md:
Use the cocoindex-code MCP server for semantic code search when:
- Searching for code by meaning or description rather than exact text
- Exploring unfamiliar parts of the codebase
- Looking for implementations without knowing exact names
- Finding similar code patterns or related functionality
Features
- Semantic Code Search: Find relevant code using natural language queries when grep doesn't work well, and save tokens immediately.
- Ultra Performant to code changes:⚡ Built on top of ultra performant Rust indexing engine. Only re-indexes changed files for fast updates.
- Multi-Language Support: Python, JavaScript/TypeScript, Rust, Go, Java, C/C++, C#, SQL, Shell
- Embedded: Portable and just works, no database setup required!
- Flexible Embeddings: By default, no API key required with Local SentenceTransformers - totally free! You can customize 100+ cloud providers.
Configuration
| Variable | Description | Default |
|---|---|---|
COCOINDEX_CODE_ROOT_PATH |
Root path of the codebase | Auto-discovered (see below) |
COCOINDEX_CODE_EMBEDDING_MODEL |
Embedding model (see below) | sbert/sentence-transformers/all-MiniLM-L6-v2 |
COCOINDEX_CODE_EXTRA_EXTENSIONS |
Additional file extensions to index (comma-separated, e.g. "inc:php,yaml,toml" — use ext:lang to override language detection) |
(none) |
COCOINDEX_CODE_EXCLUDED_PATTERNS |
Additional glob patterns to exclude from indexing as a JSON array (e.g. '["**/migration.sql", "{**/*.md,**/*.txt}"]') |
(none) |
Root Path Discovery
If COCOINDEX_CODE_ROOT_PATH is not set, the codebase root is discovered by:
- Finding the nearest parent directory containing
.cocoindex_code/ - Finding the nearest parent directory containing
.git/ - Falling back to the current working directory
Embedding model
By default - this project use a local SentenceTransformers model (sentence-transformers/all-MiniLM-L6-v2). No API key required and completely free!
Use a code specific embedding model can achieve better semantic understanding for your results, this project supports all models on Ollama and 100+ cloud providers.
Set COCOINDEX_CODE_EMBEDDING_MODEL to any LiteLLM-supported model, along with the provider's API key:
Ollama (Local)
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=ollama/nomic-embed-text \
-- cocoindex-code
Set OLLAMA_API_BASE if your Ollama server is not at http://localhost:11434.
OpenAI
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=text-embedding-3-small \
-e OPENAI_API_KEY=your-api-key \
-- cocoindex-code
Azure OpenAI
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=azure/your-deployment-name \
-e AZURE_API_KEY=your-api-key \
-e AZURE_API_BASE=https://your-resource.openai.azure.com \
-e AZURE_API_VERSION=2024-06-01 \
-- cocoindex-code
Gemini
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=gemini/text-embedding-004 \
-e GEMINI_API_KEY=your-api-key \
-- cocoindex-code
Mistral
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=mistral/mistral-embed \
-e MISTRAL_API_KEY=your-api-key \
-- cocoindex-code
Voyage (Code-Optimized)
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=voyage/voyage-code-3 \
-e VOYAGE_API_KEY=your-api-key \
-- cocoindex-code
Cohere
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=cohere/embed-english-v3.0 \
-e COHERE_API_KEY=your-api-key \
-- cocoindex-code
AWS Bedrock
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=bedrock/amazon.titan-embed-text-v2:0 \
-e AWS_ACCESS_KEY_ID=your-access-key \
-e AWS_SECRET_ACCESS_KEY=your-secret-key \
-e AWS_REGION_NAME=us-east-1 \
-- cocoindex-code
Nebius
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=nebius/BAAI/bge-en-icl \
-e NEBIUS_API_KEY=your-api-key \
-- cocoindex-code
Any model supported by LiteLLM works — see the full list of embedding providers.
Local SentenceTransformers models
Use the sbert/ prefix to load any SentenceTransformers model locally (no API key required).
Example — general purpose text model:
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=sbert/nomic-ai/nomic-embed-text-v1 \
-- cocoindex-code
GPU-optimised code retrieval:
nomic-ai/CodeRankEmbed delivers significantly better code retrieval than the default model. It is 137M parameters, requires ~1 GB VRAM, and has an 8192-token context window.
claude mcp add cocoindex-code \
-e COCOINDEX_CODE_EMBEDDING_MODEL=sbert/nomic-ai/CodeRankEmbed \
-- cocoindex-code
Note: Switching models requires re-indexing your codebase (the vector dimensions differ).
MCP Tools
search
Search the codebase using semantic similarity.
search(
query: str, # Natural language query or code snippet
limit: int = 10, # Maximum results (1-100)
offset: int = 0, # Pagination offset
refresh_index: bool = True # Refresh index before querying
)
The refresh_index parameter controls whether the index is refreshed before searching:
True(default): Refreshes the index to include any recent changesFalse: Skip refresh for faster consecutive queries
Returns matching code chunks with:
- File path
- Language
- Code content
- Line numbers (start/end)
- Similarity score
Supported Languages
| Language | Aliases | File Extensions |
|---|---|---|
| c | .c |
|
| cpp | c++ | .cpp, .cc, .cxx, .h, .hpp |
| csharp | csharp, cs | .cs |
| css | .css, .scss |
|
| dtd | .dtd |
|
| fortran | f, f90, f95, f03 | .f, .f90, .f95, .f03 |
| go | golang | .go |
| html | .html, .htm |
|
| java | .java |
|
| javascript | js | .js |
| json | .json |
|
| kotlin | .kt, .kts |
|
| lua | .lua |
|
| markdown | md | .md, .mdx |
| pascal | pas, dpr, delphi | .pas, .dpr |
| php | .php |
|
| python | .py |
|
| r | .r |
|
| ruby | .rb |
|
| rust | rs | .rs |
| scala | .scala |
|
| solidity | .sol |
|
| sql | .sql |
|
| swift | .swift |
|
| toml | .toml |
|
| tsx | .tsx |
|
| typescript | ts | .ts |
| xml | .xml |
|
| yaml | .yaml, .yml |
Common generated directories are automatically excluded:
__pycache__/node_modules/target/dist/vendor/(Go vendored dependencies, matched by domain-based child paths)
Troubleshooting
sqlite3.Connection object has no attribute enable_load_extension
Some Python installations (e.g. the one pre-installed on macOS) ship with a SQLite library that doesn't enable extensions.
macOS fix: Install Python through Homebrew:
brew install python3
Then re-install cocoindex-code (see Get Started for install options):
Using pipx:
pipx install cocoindex-code # first install
pipx upgrade cocoindex-code # upgrade
Using uv (install or upgrade):
uv tool install --upgrade cocoindex-code --prerelease explicit --with "cocoindex>=1.0.0a24"
Large codebase / Enterprise
CocoIndex is an ultra effecient indexing engine that also works on large codebase at scale on XXX G for enterprises. In enterprise scenarios it is a lot more effecient to do index share with teammates when there are large repo or many repos. We also have advanced features like branch dedupe etc designed for enterprise users.
If you need help with remote setup, please email our maintainer linghua@cocoindex.io, happy to help!!
License
Apache-2.0
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