secop-mcp
Related Servers
Alternatives to secop-mcp
No user-submitted related servers found.
Related Servers
- AlicenseBqualityCmaintenanceExposes Colombia's SECOP II and Colombia Compra Eficiente procurement layers to LLM agents, enabling SODA SoQL process and contract searches, deep opportunity inspection and ASP.NET spidering, COP budget analytics, and generation of RAG-ready vector chunks and feeds.8MIT
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query Colombian government procurement data via MCP tools or natural language questions.428 npmMIT
- AlicenseAqualityDmaintenanceAn MCP server to query Colombian public procurement data from SECOP I and II in real time, enabling contract research, transparency oversight, and data journalism.1070 PyPI2MIT
- AlicenseNot gradedqualityBmaintenanceEnables agents to look up Colombian company registry, sanctions, restricted-party lists, and public procurement records — including contracts, bidders, consortia, and process documents — all cross-referenced by NIT and returned with the official source and capture date behind every figure.MIT
- -licenseNot gradedqualityNot gradedmaintenanceEnables Claude, ChatGPT, and other MCP-compatible assistants to query public Colombian data sources—including SECOP contracting, OFAC sanctions screening, RUES companies, judicial processes, and a local jurisprudence index—with source, URL, consultation date, and verification status in responses.-
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query Ecuador government procurement (SERCOP/Compras Públicas) data without API keys, via natural language or direct tools.273 npmMIT
TDQS
Scored across 3 tools
The three tools serve clearly separate roles: describe_dataset is schema discovery, find_entity resolves an entity name to a NIT against a local directory, and query_contracts runs the actual data query. The find_entity description explicitly clarifies it does not touch the dataset, removing any overlap with query_contracts.
All three names follow a clean verb_noun snake_case pattern (describe_dataset, find_entity, query_contracts) with no stylistic deviations or mixing of conventions.
Three focused tools for a single-domain dataset server is well-scoped—each one (understand schema, resolve entity, query) earns its place with no redundancy. It leans slightly minimal, but the workflow is coherent.
The surface covers the core lifecycle for a data query server: understand the schema, resolve entities, and query with filters/aggregates/ordering. A few gaps remain, such as no distinct-values helper or paging beyond the 100-row cap, but agents can work around them.