A
licenseNot graded
qualityD
maintenanceEnables interaction with Azure AI Agent Service by automatically discovering agents and creating MCP tools for querying and managing agent workflows.
1
MIT
Foundry Agents MCP Server
by denniszielke
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TDQS
A3.6/5.0
Scored across 10 tools
Disambiguation3/5
The agents_* and workflows_* tools are fairly distinguishable, but there's notable overlap between index_ingest_project_log and search_add_to_vector_db — both add a document to the same vector index. search_vector_db vs index_* tools are clear, but the ingest/add duplication causes potential misselection.
Naming Consistency3/5
The server mixes three namespaces: agents_*, index_*, and search_*, each with a verb_noun pattern. However, search_vector_db and search_add_to_vector_db break consistency — one names the action (search) while the other uses search_ as a namespace prefix, so search_* doesn't consistently mean a namespace or an action.
Tool Count4/5
10 tools is a reasonable and well-scoped count for a server handling both agent invocation and vector-database search. Each tool has a clear role in the two primary workflows, though the redundant ingest/add tools pad the count slightly.
Completeness4/5
The agent workflow covers list/invoke/status/result, which is complete for async invocation. The vector DB side has create-index, ingest, add, and search. Minor gaps exist — there's no delete or update for vector documents, and the result retrieval is separated from status with no explicit error-handling tool — but core lifecycle needs are met.
Maintenance
ActivityInactive
ResponsivenessNo issues