MCP server for searching Google Scholar — papers, authors, citations, and BibTeX
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"google-scholar-search-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# google-scholar-search-mcp An MCP (Model Context Protocol) server for searching Google Scholar, built for AI assistants and automation workflows that need papers, authors, citations, and BibTeX entries. ## Table of Contents 1. [Features](#features) 2. [Installation](#installation) 3. [Configuration](#configuration) 4. [Usage](#usage) 5. [Examples](#examples) 6. [Rate Limiting](#rate-limiting) 7. [Troubleshooting](#troubleshooting) 8. [Contributing](#contributing) ## Features - **Paper Search**: Query Google Scholar by keyword with filtering, sorting, and pagination - **Author Lookup**: Find researcher profiles with publication lists and h-index metrics - **Citation Tracking**: Retrieve papers that cite a given work - **Paper Details**: Get full metadata, citations-per-year graphs, and public access info - **BibTeX Export**: Generate citation entries in BibTeX format - **Bulk Search**: Batch search multiple queries with automatic rate limiting - **Rate Limiting**: Built-in delays between requests to avoid being blocked - **Proxy Support**: Optional proxy configuration (free, single, or ScraperAPI) ## Installation ### Requirements - `Python 3.11` or later - Dependencies: `mcp[cli]>=1.4.0`, `scholarly>=1.7.11`, `pydantic>=2.0` (see [pyproject.toml](./pyproject.toml)) - project uses `uv` for dependency management ### Install it from PyPI ```bash pip install google-scholar-search-mcp ``` ### Build from Source ```bash git clone https://github.com/LWaetzig/google-scholar-search-mcp.git cd google-scholar-search-mcp pip install -e . ``` **Note:** This server uses the [scholarly](https://scholarly.readthedocs.io/) library to access Google Scholar. Respect Google's Terms of Service and use rate limiting appropriately to avoid being blocked. ## Configuration Configure the MCP server via environment variables: | Variable | Default | Description | |----------|---------|-------------| | `GS_MIN_DELAY` | `5.0` | Minimum seconds between requests | | `GS_MAX_DELAY`…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.