The fogx/typesense-mcp project provides a community Model Context Protocol server for querying and managing Typesense search indices via stdio. Configure a TOML file with one or more `[[sources]]` blocks (id, host, api_key, collections patterns, optional readonly, port, protocol) and launch with `npx -y typesense-mcp path/to/typesense-mcp.toml` per the README. Tools include `search` for full-text, vector, or hybrid search; `lookup` for collections, schema, documents, counts, aliases, and synonyms; and `manage` for upserts, deletes, collection/synonym/alias writes when at least one source is not readonly. Collection patterns gate access; readonly sources block writes and hide `manage` when all sources are readonly. A `collection://{source}/{collection}` resource exposes field schemas. Pairs naturally with the Typesense tool entry on this site for agent-driven index exploration.
Use cases
- Let agents run hybrid or vector Typesense searches with collection-scoped keys
- Inspect schemas via collection:// resources before drafting YQL-like filter queries
- Use readonly production sources for safe analytics while staging sources allow manage writes
- Compare typesense-mcp against meilisearch-mcp or algolia-productivity-mcp during evaluations
- Prototype agent search QA over timestamped collection prefixes in TOML config
Key features
- Claude Desktop
- Cursor
- VS Code
Frequently Asked Questions
- Is this an official Typesense MCP?
- No—Typesense does not list fogx/typesense-mcp as an official server; it is a community MCP documented in the GitHub README.
- How do I prevent agents from deleting collections?
- Set `readonly = true` on production sources or scope collections patterns; manage is omitted entirely if all sources are readonly.
- Does it support hybrid search?
- README documents the search tool for text, vector (by embedding or document ID), and hybrid search with alpha blending.
Related
Related
3 Indexed items
Meilisearch MCP Server
Meilisearch maintains an official Model Context Protocol server in meilisearch/meilisearch-mcp, documented at meilisearch.com/blog/introducing-mcp-server. The Python stdio server connects MCP clients to any running Meilisearch instance via `MEILI_HTTP_ADDR` and optional `MEILI_MASTER_KEY`, with `update-connection-settings` to switch hosts mid-session. Tools cover index management, document ingestion, search (filters, sorting, facets, semantic/hybrid), settings, API keys, tasks, and health checks per the README. Install paths include `uvx meilisearch-mcp`, pip, source, and Docker (`getmeili/meilisearch-mcp`). Meilisearch notes the server is development-oriented and that native Meilisearch MCP transport support is coming.
Algolia Productivity MCP Server
Algolia documents an official managed Model Context Protocol server at algolia.com/doc/guides/model-context-protocol/productivity-mcp. Connect MCP clients to the remote HTTP endpoint `https://mcp.algolia.com/mcp` with OAuth (enable under Generate AI in the Algolia dashboard; sign in when prompted so the MCP inherits your account permissions). Productivity MCP is user-scoped and read-only per docs—tools cover search (`algolia_search_list_indices`, `algolia_search_index`, `algolia_search_for_facet_values`), Recommend (`algolia_recommendations`), and analytics helpers such as top searches, no-click rates, filter usage, and user counts. Algolia docs distinguish this from Algolia Public MCP for application-scoped, curated index exposure to external agents. Supported clients include ChatGPT, Claude, Claude Code, Cursor, Gemini CLI, VS Code, and OpenAI Playground.
Elastic Agent Builder MCP Server
Elastic documents the recommended Agent Builder Model Context Protocol endpoint at `{KIBANA_URL}/api/agent_builder/mcp` (or `{KIBANA_URL}/s/{SPACE_NAME}/api/agent_builder/mcp` for custom Kibana spaces) per elastic.co/docs/explore-analyze/ai-features/agent-builder/mcp-server. The MCP server exposes built-in and custom Agent Builder tools to Claude Desktop, Cursor, VS Code, and other MCP clients via `npx mcp-remote` with an `Authorization: ApiKey` header. API keys must include the Kibana application privilege `feature_agentBuilder.read` or clients receive HTTP 403. Elastic notes the legacy `elastic/mcp-server-elasticsearch` project is deprecated in favor of this endpoint on Elastic 9.2+ and Elasticsearch Serverless; docs recommend least-privilege index scopes and API key expiration.