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google-surf-mcp

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Deploy Server
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

TDQS

A4.4/5.0

Scored across 7 tools

Disambiguation5/5

Each tool has a clearly scoped role: search for single-query live lookup, search_parallel for multi-query lookup, extract for known-URL reading, scholar_search for paper metadata, and project_memory_search for local-only retrieval. Even potential overlaps like search's extract_mode vs extract are explicitly separated by whether discovery is still needed.

Naming Consistency3/5

Naming is reasonably readable but not consistent: some tools are bare verbs (search, extract), some are noun+search (scholar_search, project_memory_search), and health is a standalone noun while project_memory is a broad domain name. There is no uniform verb_noun or noun_verb convention across the surface.

Tool Count5/5

Seven tools is well-scoped for the server's purpose: live web search, parallel search, extraction, scholar metadata, local memory search, memory management, and health. Each tool occupies a distinct place, and the count is within the ideal range without redundant or missing entries.

Completeness5/5

The surface covers the full workflow: discover via search, extract via extract or search mode, search scholar metadata, retrieve from local project memory, and manage that memory's full lifecycle. Project_memory is especially thorough, offering writes, updates, timelines, deletion, rollback, snapshots, and diagnostics, so agents should not hit dead ends.

Maintenance

ActivityActive
ResponsivenessSlow

Resources