{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_48cfhbhjhnxn","handle":"iflow-mcp-philschmid-gemini-docs-mcp","url":"https://wellknown.network/agents/iflow-mcp-philschmid-gemini-docs-mcp","links":{"self":"https://wellknown.network/agents/iflow-mcp-philschmid-gemini-docs-mcp/record.json","html":"https://wellknown.network/agents/iflow-mcp-philschmid-gemini-docs-mcp","markdown":"https://wellknown.network/agents/iflow-mcp-philschmid-gemini-docs-mcp/record.md","api":"https://wellknown.network/api/v1/agents/iflow-mcp-philschmid-gemini-docs-mcp","status":"https://wellknown.network/api/v1/agents/iflow-mcp-philschmid-gemini-docs-mcp/status","claim":"https://wellknown.network/agents/iflow-mcp-philschmid-gemini-docs-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/iflow-mcp-philschmid-gemini-docs-mcp/claim.json","badge":"https://wellknown.network/agents/iflow-mcp-philschmid-gemini-docs-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/iflow-mcp-philschmid-gemini-docs-mcp/history","tools":"https://wellknown.network/api/v1/agents/iflow-mcp-philschmid-gemini-docs-mcp/tools"},"ard":{"identifier":"urn:air::server:iflow-mcp-philschmid-gemini-docs-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"iflow-mcp_philschmid-gemini-docs-mcp","summary":"MCP server for searching Google Gemini API documentation","description":"# Gemini Docs MCP Server\n\nA remote HTTP MCP server that provides tools to search and retrieve Google Gemini API documentation. The server exposes the MCP protocol at the `/mcp` endpoint and can be deployed to Cloud Run or other containerized platforms. It also supports local stdio mode for development.\n\n<a href=\"https://glama.ai/mcp/servers/@philschmid/gemini-api-docs-mcp\">\n  <img width=\"380\" height=\"200\" src=\"https://glama.ai/mcp/servers/@philschmid/gemini-api-docs-mcp/badge\" alt=\"Gemini Docs Server MCP server\" />\n</a>\n\n-   **Search Documentation**: Full-text search across all Gemini documentation pages.\n-   **Get Capabilities**: List available documentation pages or retrieve content for a specific page.\n-   **Get Current Model**: Quickly access documentation for current Gemini models.\n-   **Automatic Updates**: Scrapes and updates documentation on server startup.\n\n```mermaid\nsequenceDiagram\n    participant Client as MCP Client / IDE\n    participant Server as FastMCP Server\n    participant DB as SQLite Database\n\n    Client->>Server: call_tool(\"search_documentation\", queries=[\"embeddings\"])\n    Server->>DB: Full-Text Search for \"embeddings\"\n    DB-->>Server: Return matching documentation\n    Server-->>Client: Return formatted results\n```\n## How it Works\n\n1.  **Ingestion**: On startup, the server fetches `https://ai.google.dev/gemini-api/docs/llms.txt` to get a list of all available documentation pages.\n2.  **Processing**: It then concurrently fetches and processes each page, extracting the text content.\n3.  **Indexing**: The processed content is stored in a local SQLite database with a Full-Text Search (FTS5) index for efficient querying.\n4.  **Searching**: When you use the `search_documentation` tool, the server queries this SQLite database to find the most relevant documentation pages.\n\n## Installation\n\n### Option 1: Use `uvx` (Recommended)\n\nYou can use `uvx` to run the server directly without explicit installation. This is the easiest way to get started.\n\n```bas…","publisher":null,"homepage":null,"repository":null,"version":"0.1.0","license":null,"protocols":["mcp"],"tags":["mcp"],"pricing":null,"endpoints":[{"url":"pypi:iflow-mcp_philschmid-gemini-docs-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","summary":"pypi","version":"pypi","description":"pypi"}},"derived":{"capabilities":[{"slug":"dev.docs-lookup","name":"Documentation Lookup","confidence":1,"provenance":"derived"},{"slug":"code.documentation","name":"Code Documentation","confidence":0.871,"provenance":"derived"},{"slug":"data.database","name":"Databases","confidence":0.802,"provenance":"derived"}],"categories":["code","data","dev"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"iflow-mcp_philschmid-gemini-docs-mcp","registry":"pypi","observedAt":"2026-09-15T19:23:31.039Z","publishedAt":"2026-02-12T16:21:07.141885Z","latestVersion":"0.1.0"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"iflow-mcp_philschmid-gemini-docs-mcp","url":"https://pypi.org/project/iflow-mcp_philschmid-gemini-docs-mcp/","firstSeenAt":"2026-09-09T20:25:03.012Z","fetchedAt":"2026-09-15T19:22:38.492Z","normalizedAt":"2026-09-15T19:22:38.492Z"}]},"firstSeenAt":"2026-09-09T20:25:03.012Z","updatedAt":"2026-09-15T19:23:31.039Z"}