Turbopuffer MCP Server
Click on "Deploy 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., "@Turbopuffer MCP ServerSearch the 'documents' namespace for similar vectors"
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.
turbopuffer-mcp
A Turbopuffer MCP server built with dedalus-mcp and DAuth-style credential exchange.
This server follows the same DAuth north-star pattern as x-api-mcp:
Credentials are provided by clients at runtime.
The server declares a
ConnectionwithSecretKeys.Tool calls dispatch through Dedalus secure connection handles.
Features
DAuth-compatible API key authentication (
TURBOPUFFER_API_KEY).Configurable Turbopuffer region/base URL via
TURBOPUFFER_BASE_URL.Read + write tool coverage for the core Turbopuffer API.
Includes a smoke ping tool for quick MCP handshake validation.
Related MCP server: InfluxDB MCP Server
Setup
Create a Turbopuffer API key.
Copy env template:
cp .env.example .envRequired:
TURBOPUFFER_API_KEY(provided by the MCP client via DAuth credentials in production flows)
Optional:
TURBOPUFFER_BASE_URL(defaults tohttps://gcp-us-central1.turbopuffer.com)DEDALUS_AS_URL(defaults tohttps://as.dedaluslabs.ai)HOST(defaults to127.0.0.1)PORT(defaults to8080)
Run
uv run python src/main.pyTool Surface
turbopuffer_list_namespacesturbopuffer_get_namespace_metadataturbopuffer_get_namespace_schematurbopuffer_update_namespace_schematurbopuffer_writeturbopuffer_queryturbopuffer_multi_queryturbopuffer_explain_queryturbopuffer_delete_namespaceturbopuffer_cache_warmturbopuffer_measure_recallturbopuffer_export_documents(deprecated Turbopuffer endpoint compatibility)smoke_ping
Notes
Turbopuffer has both
/v1and/v2endpoints. This server mirrors the live docs/API split:Namespace listing/metadata/schema/cache-warm/recall/export use
/v1.Write/query/delete/explain use
/v2.
The export endpoint is deprecated in Turbopuffer docs in favor of paging query APIs, but is still exposed here for compatibility.
This server cannot be deployed
Maintenance
Related MCP Connectors
Operate your Vector Panda collections: search and upsert vectors, schema, measured indexes, exports.
A collaborative substrate over your data: vector, knowledge graph, SQL, geospatial, streaming.
Persistent memory for AI agents. Search and store durable facts, preferences and decisions.
Provides capabilities that let LLM agents perform a range of infrastructure management tasks.
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