Periscope MCP
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Alternatives to Periscope MCP
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Related Servers
- AlicenseNot gradedqualityBmaintenanceEnables AI agents to query a read-only data surface through typed tools, enforcing caller-specific row access, field masking, and withheld-row disclosure so they can retrieve entitled information without writes or silent data leakage.MIT
- AlicenseNot gradedqualityDmaintenanceEnables AI agents to securely query VAST Data databases for schema, metadata, and sample data via read-only SQL and MCP resources.MIT
- AlicenseNot gradedqualityAmaintenanceGives AI agents read-only access to Postgres with parser-checked queries, hidden tables and columns, row limits and timeouts, caller-bound Row-Level Security, and a tamper-evident audit log.MIT
- AlicenseNot gradedqualityBmaintenanceGives AI agents read-only access to any QuestDB instance, enabling schema discovery, time-series querying, and monitoring of partitions, WAL state, symbols, and ingestion health through MCP.Apache 2.0
- AlicenseNot gradedqualityAmaintenanceProvides fail-closed, read-only PostgreSQL and MongoDB access for AI agents via MCP, enabling structured data inspection and bounded queries without mutation capabilities.MIT
- AlicenseNot gradedqualityCmaintenanceEnables analytics agents to run validated read-only SQL against a warehouse API with enforced row limits, required JSON responses, and secret-safe audit metadata.MIT
TDQS
Scored across 6 tools
The tools split cleanly along the query lifecycle: discovery (list_sources, describe), execution (query, cancel_query), monitoring (get_result) and retrieval (read_result), and each description explains its role in the sequence. The only mild overlap is get_result vs read_result, which sound similar (status/manifest vs inline rows) and rely on the descriptions to separate.
Most names are consistent snake_case verb_noun (list_sources, get_result, read_result, cancel_query), which is predictable. The two bare verbs 'describe' and 'query' deviate slightly from the pattern but remain readable and verb-first.
Six tools is well-scoped for a read-only federated query service; each one maps to a distinct lifecycle stage (list, describe, start, poll, read, cancel) with no filler. Nothing feels thin or bloated.
The full async query lifecycle is covered: source discovery, metadata drill-down, query start, status/progress polling, windowed row/blob retrieval with download manifest, and cancellation. No obvious dead ends for a read-only query server.