hbg/mcp-paperswithcode
by Various
An unofficial MCP interface to interact with the PapersWithCode API
MCP
hbg/mcp-paperswithcode
Added 1 June 2026
Overview
An unofficial MCP interface for interacting with the PapersWithCode API. It provides a Model Context Protocol server that allows developers to query research papers, code implementations, and benchmarks programmatically.
Best for
Best for
Developers building AI agents or tools that need to programmatically access papers, code, and benchmarks from PapersWithCode
Use cases
- Retrieve papers by topic or keyword for research workflows
- Fetch code repositories associated with published papers
- Search and compare benchmark results across datasets
How to use
Install
npx -y @smithery/cli install @hbg/mcp-paperswithcode --client claude Tools exposed
search_papersget_paperread_paper_from_urllist_paper_resultslist_paper_taskslist_paper_methodslist_paper_repositorieslist_paper_datasetssearch_research_areasget_research_arealist_research_area_taskssearch_authorsget_paper_authorlist_papers_by_author_idlist_papers_by_author_namelist_conferencesget_conferencelist_conference_proceedingsget_conference_proceedinglist_conference_papers
Tested with
Claude Desktop
Notes
An unofficial MCP interface for interacting with the PapersWithCode API. It provides a Model Context Protocol server that allows developers to query research papers, code implementations, and benchmarks programmatically.
22 stars on GitHub. Last updated 2025-06-07. Licensed MIT.
Use cases
- Retrieve papers by topic or keyword for research workflows
- Fetch code repositories associated with published papers
- Search and compare benchmark results across datasets
Pros
- Lightweight Python implementation with minimal dependencies
- Follows the MCP standard for easy integration with AI agents
- Direct access to PapersWithCode’s structured metadata
Cons
- Unofficial tool with limited community support (22 stars)
- Relies on the PapersWithCode API which may have rate limits or change
- Documentation is sparse, requiring familiarity with both MCP and the API
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Lightweight Python implementation with minimal dependencies
- Follows the MCP standard for easy integration with AI agents
- Direct access to PapersWithCode's structured metadata
Cons
- Unofficial tool with limited community support (22 stars)
- Relies on the PapersWithCode API which may have rate limits or change
- Documentation is sparse, requiring familiarity with both MCP and the API
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