connerlambden/bgpt-mcp
by Various
Scientific paper search API for AI agents: REST, Python, OpenAPI, and MCP with structured full-text evidence.
MCP
connerlambden/bgpt-mcp
Added 1 June 2026
Overview
Provides a scientific paper search API designed for AI agents. Supports REST, Python, OpenAPI, and the Model Context Protocol (MCP) to deliver structured full-text evidence from papers.
Best for
Best for
Developers building AI agents that need structured access to scientific papers
Use cases
- Searching scientific literature programmatically
- Integrating paper evidence into AI agent workflows
- Building research tools with structured citation data
Notes
Provides a scientific paper search API designed for AI agents. Supports REST, Python, OpenAPI, and the Model Context Protocol (MCP) to deliver structured full-text evidence from papers.
24 stars on GitHub. Last updated 2026-05-26. Licensed MIT.
Use cases
- Searching scientific literature programmatically
- Integrating paper evidence into AI agent workflows
- Building research tools with structured citation data
Pros
- Multiple interface options (REST, Python, OpenAPI, MCP)
- Returns structured full-text evidence
- Open source with JavaScript implementation
Cons
- Small community (24 stars) may indicate limited adoption
- Documentation and stability may be limited
- Requires self-hosting or API key setup
Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.
Pros
- Multiple interface options (REST, Python, OpenAPI, MCP)
- Returns structured full-text evidence
- Open source with JavaScript implementation
Cons
- Small community (24 stars) may indicate limited adoption
- Documentation and stability may be limited
- Requires self-hosting or API key setup
Pairs with
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