turbovec-mcp
Provides tools for indexing and searching code using OpenAI-compatible embedding endpoints, enabling semantic code search on local repositories.
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@turbovec-mcpfind where we parse the CSV file"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
turbovec-mcp
Local semantic code search over MCP, backed by turbovec (Google's TurboQuant: ~16x vector compression, fast on Apple Silicon). Bring your own OpenAI-compatible embeddings endpoint - nothing leaves your machine.
code -> chunker -> [your embeddings endpoint] -> turbovec index -> searchembedder: any OpenAI-compatible
/v1/embeddings(a llama.cpp server, etc). Dimension is auto-detected.store: turbovec
IdMapIndex, persisted per-repo under.turbovec/.orchestrator: this MCP server (chunk, embed, index, search).
Install / run
uvx turbovec-mcp # run directly, no install (recommended)
# or
pipx install turbovec-mcpRequires a running embeddings endpoint. Example with llama.cpp:
llama-server -m nomic-embed-text-v1.5.Q8_0.gguf --embedding --pooling mean --port 8081Related MCP server: punt-quarry
Configure (environment)
var | default | meaning |
|
| OpenAI-compatible base URL |
|
| model name sent in the request |
|
| bearer token (unused locally, must be non-empty) |
| auto | prefix for documents; auto = |
| auto | prefix for queries; auto = |
|
| embedding inputs per request |
|
| embedding request timeout (seconds) |
|
| hard char cap per embedded input |
|
| turbovec quantization bits (2 or 4) |
|
| lines per chunk |
|
| overlap between chunks |
|
| skip files larger than this |
| "" | comma list of extra extensions to index |
| "" | comma list of extra dirs to skip |
With the default nomic model the prefixes auto-resolve, so a bare setup needs no env exports at all. Set the env vars (or pass another model) only for a non-nomic embedder.
Setup
With the default nomic embedder this is the whole flow - no config editing, no env exports:
# (a) run the embeddings endpoint
llama-server -m nomic-embed-text-v1.5.Q8_0.gguf --embedding --pooling mean --port 8081
# (b) register + seed file selection (writes .mcp.json AND opencode.jsonc)
turbovec-mcp init .
# (c) build the index
turbovec-mcp index .
# (d) restart your agent so it picks up the new MCP serverinit registers the turbovec MCP server into both project-local configs
automatically:
<repo>/.mcp.json(Claude Code) - merged in, other servers preserved.<repo>/opencode.jsonc- created if absent, surgically merged if it's plain JSON. Only an existing opencode.jsonc that contains comments is left untouched; in that one caseinitprints a snippet to paste under its"mcp"key. Your global~/.config/opencodeconfig is never touched.
The registered command is the absolute path to the installed turbovec-mcp
(reliable today); once published to PyPI you can use uvx turbovec-mcp instead.
Pass --no-register to seed config.json only and skip writing both config
files.
Chunking
AST-aware via tree-sitter. Each function / class / method that fits the embedder becomes one chunk on clean boundaries; a god-class too large to embed whole is split into its methods; any lines not covered by a definition (imports, top-level code, a giant leaf function) are line-windowed, so coverage is total. Unsupported languages / parse failures fall back to plain line-window chunking - nothing is skipped.
Supported out of the box: Python, JS/TS/TSX, Go, Rust, Java, Kotlin, Scala,
Swift, C/C++, C#, Ruby, PHP, Lua, Perl, R, Julia, Bash, Fortran (f90/f95).
Add more file extensions with TURBOVEC_EXTRA_EXTENSIONS.
Tools
Workflow is two steps: tv_search for terse triage, then tv_fetch to read
the locations you picked.
tv_search(query, k=10, path=".")- semantic search. Terse: each hit isscore+ location (path:start-end) + the chunk's signature line. No source bodies.tv_fetch(locations, path=".")- full source for a list of"path:start-end"locations (the onestv_searchreturned).tv_index(path=".")- (re)build the index for a repo. Run once before searching, and after large changes.tv_status(path=".")- whether a repo is indexed + basic stats.
The index lives in <repo>/.turbovec/ - add it to .gitignore.
File selection
<repo>/.turbovec/config.json is the source of truth for which files get
indexed: its include / exclude glob lists decide everything. Seed it with:
turbovec-mcp init [path] # seed config + register both agents (-f to rewrite)init does two things:
Seeds
<repo>/.turbovec/config.json, fillingexcludefrom the default skip dirs plus any nested.gitignores in the tree.Registers the turbovec MCP server into project-local
<repo>/.mcp.json(Claude Code) and<repo>/opencode.jsonc(opencode). Both preserve any other servers and are idempotent; pass-fto rewrite the entry. The registeredcommandis the absolute path to the installedturbovec-mcp. opencode.jsonc is created if absent and surgically merged if it's plain JSON; an existing comment-bearing opencode.jsonc is left alone and a paste-snippet is printed instead. The global~/.config/opencodeconfig is never touched.
Pass --no-register to seed config.json only and skip writing both config
files.
Edit the globs, then run turbovec-mcp index.
CLI
For testing from the terminal:
turbovec-mcp init [path] # seed config + register .mcp.json + opencode.jsonc; --no-register to skip
turbovec-mcp index <path> # build/rebuild the index
turbovec-mcp status <path>
turbovec-mcp search <path> <query> [-k N] # terse: score path:lines signature
turbovec-mcp fetch <path> <location>... # full source for path:start-endLicense
BSD-3-Clause
This server cannot be installed
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
Latest Blog Posts
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/potatofacee/turbovec-mcp'
If you have feedback or need assistance with the MCP directory API, please join our Discord server