MCP server for hybrid search capabilities in Meilisearch, combining keyword and vector search
Single tool 'hybrid_search' with well-structured schema and reasonable descriptions. Tool naming is clear and action-oriented (verb_noun pattern). Parameters have type constraints (min/max bounds) and mostly good descriptions. However, output schema is not formally documented, tool returns JSON text rather than structured typed output. Parameter descriptions could be more concise and action-focused. Error handling exists but lacks recovery guidance. Overall solid for a single-tool server but missing production-grade documentation polish.
Hybrid search your documents in Meilisearch index
Output schema not formally documented. Tool returns JSON text (mcp.NewToolResultText) rather than structured typed result with schema. LLMs cannot plan downstream calls or validate expected fields without a declared output schema.
Parameter descriptions contain implementation details and tuning guidance that should be in usage notes, not param descriptions. E.g., 'If the `_rankingScore` in results is low, try adjusting to 0.8 or 0.2...' is verbose and mixes UI guidance with parameter semantics.
No recovery guidance in error handling. When 'no results found' or embedder is missing, tool returns plain error text without suggesting next steps (e.g., 'Try broader keywords' or 'Configure MEILI_EMBEDDER environment variable').
Inferred effective spec: <=2025-11-25.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | D | 57 | <=2025-11-25 | v2 |
| 2026-03-09 | F | 41 | - | v1 |
Mutual parameter dependency not clearly documented. 'filterable_attribute' and 'filter_word' are mutually dependent, both must be present to apply a filter, but this constraint is only implied in descriptions, not explicitly stated as a hard requirement.
Tool description lacks WHEN to use it and alternatives. Describes WHAT (hybrid search) but not WHEN an LLM should prefer this over keyword-only or semantic-only search. No guidance on typical use cases.