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ebird-mcp-server

This is a Model Context Protocol (MCP via Anthropic) Server for the EBird API v2.0 (Cornell's Lab of Ornithology) which acts Natural Language Interface to LLMs like Claude to interact with API

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What's in it

Data offered docs-verified
recent bird observations by region · notable/rare sightings · species-specific observations · observations near coordinates · historical observations · regional arrival/departure statistics · species taxonomy · birding hotspot information
Coverage llm-inferred
Global (ENTRY regions metadata); queries use region codes such as US-CA
Formats llm-inferred
MCP stdio
Access docs-verified
eBird API token required (sign up for an eBird account, then request a token); server code MIT licensed

Useful for

Use cases llm-inferred
Pre-development bird baseline from recent and historic observations near a site (ecology scoping) · Notable/rare species check within a search radius for ecological constraints screening · Species-specific occurrence records for habitat assessment context · Hotspot identification to inform bird survey planning
Audience llm-inferred
ecologists · ecological consultants · environmental planners

Limitations

Constraints llm-inferred
Requires an eBird API token; ENTRY auth field is null but docs say a token is needed · Docs have the token hard-coded in server.py (line 15), so the token sits in source code · Requires Python 3.12+, uv or pip, git, and Claude Desktop (local install) · Claude Desktop config examples are given for Windows and Mac-OS only · Region codes must be valid or no data is returned · UK coverage is not stated in the docs · No rate limits, resolution or update frequency documented
Licence
Unknown — check provider terms
Authentication
Unknown — review source docs
GitHub stars
3
Last commit
21/07/2025
Last successful page check
14/10/2026
Page health
healthy
Package
pypi:uv
Verification
Not independently verified

Auto-extracted, unverified fields: tools, install, auth. Check upstream documentation.

Provenance & evidence

Tools/install/auth auto-extracted from README; quality score heuristic (stars, recency, tool count, licence).

Metadata observed 15/10/2026 · research sweep: github-search