evidence-mcp
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- FlicenseNot gradedqualityAmaintenanceEnables AI assistants to execute SQL, explore database schemas and sample data, inspect system metrics, and generate Plotly charts from query results.-
- FlicenseNot gradedqualityAmaintenanceIt enables AI assistants to execute SQL, explore databases and schemas, access system metrics, retrieve table and database overviews, and generate Plotly charts from query results.-
- FlicenseNot gradedqualityAmaintenanceEnables AI assistants to execute SQL, explore schemas, retrieve internal metrics, generate Plotly charts, and obtain table/database overviews from a connected data warehouse.-
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- FlicenseBqualityDmaintenanceEnables AI assistants to interact with GitHub repositories, Confluence documentation, and Databricks Unity Catalog through comprehensive tools for code exploration, documentation retrieval, and data schema management.19-
- AlicenseAqualityDmaintenanceEnables AI assistants to connect to and interact with PostgreSQL, MySQL, SQLite, and MongoDB databases through natural language, supporting schema exploration, query execution, data export, and more.13MIT
TDQS
Scored across 4 tools
Tools are mostly distinct: debug_code analyzes errors, edit_page modifies content, get_metadata queries schema, read_docs fetches documentation. Minor overlap between debug_code and edit_page as both involve page content, but their purposes are clear.
All tool names follow a consistent verb_noun pattern in lowercase with underscores: debug_code, edit_page, get_metadata, read_docs. No deviation.
Four tools is well-scoped for an Evidence MCP server, covering core needs like debugging, editing, schema discovery, and documentation. Not too few or too many.
Significant gaps: missing tools for creating, listing, or deleting pages, and no tool to run queries or fetch actual data from the database. The surface covers only partial workflows, likely causing agent failures in common tasks.