MCP server that delegates web search, audio/video understanding, and massive-context tasks to Google Gemini.
Five tools with complete descriptions and clear naming. All tools follow verb_noun pattern (gemini_*). Descriptions are well-written (100-200 chars, within baseline 194 avg). However, input schemas lack critical details: no type constraints (enums, min/max), no parameter descriptions beyond bare strings, and no output schemas documented. Error handling exists (withGeminiErrorHandling wrapper) but lacks recovery guidance. Tools are read-only (good for safety) but lack idempotent/destructive annotations. Composition is sound, each tool has one responsibility. Missing: pagination for massive_context results, per-item success/failure for batch operations.
Uploads a local audio file to Gemini for transcription, tone analysis, or summarization — useful for meeting recordings, voice memos, or audio you cannot natively listen to.
Sends large text files, logs, or PDFs to Gemini's large context window and returns a compressed, targeted summary based on your extraction request — use this instead of reading huge files directly to avoid consuming your own context budget.
Turns a raw, unstructured task idea into a polished, structured Master Prompt engineered specifically to guide Claude through executing it well — applying Anthropic's own prompt-engineering techniques (role definition, XML structuring, positive framing, task-adaptive guidance for UI/backend/writing/agentic work) via Gemini acting as an expert meta-prompter. Use this before starting a complex, ambiguous, or high-stakes task to get a better-specified brief.
Uploads a local video file to Gemini and analyzes it against a specific prompt — useful for reviewing UI walkthroughs, screen recordings, or events within a video that you cannot natively watch.
Input schemas lack type constraints and parameter descriptions. 'query' and 'filePath' parameters have descriptions, but no enums, min/max lengths, or format constraints. LLMs cannot validate inputs before calling.
No output schemas documented. LLMs cannot plan downstream operations or extract structured data. Tools return text only; no field definitions for parsed results.
massive_context tool accepts array of filePaths but no pagination or result limit documented. Large analyses could return unbounded text, exhausting context windows.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-23 | D | 55 | 2026-07-28+ | v2 |
Searches the live web via Gemini's Google Search grounding and returns a synthesized, up-to-date answer with cited source URLs. Use this for anything requiring current information beyond your training data (news, prices, recent releases, documentation, etc.).
Error handling wraps exceptions but lacks recovery guidance. classifyErrorMessage() returns status codes and generic messages; does not suggest next steps (e.g. 'Try search_users() first').
Tool annotations missing. No readOnlyHint, destructiveHint, or idempotentHint declared. All tools are read-only but this is not signaled to clients.