Semantic MCP tool discovery gateway — find tools by intent, not memory. Zero-prerequisite npx install (verified binary launcher).
Tool Compass demonstrates solid definition quality across 19 tools with consistent naming, reasonable descriptions, and complete input schemas. All tools follow verb-noun patterns (search_, list_, get_, create_, update_, delete_, archive_, restore_, prepare_, reindex_, generate_). Descriptions are present and contextual (average ~80-120 chars), explaining WHAT the tool does and its domain (Bridge content management, semantic search, project/session orchestration). Input schemas are fully specified with types and parameter descriptions. However, there are systematic gaps: (1) NO output schemas documented anywhere, LLMs cannot infer what fields these tools return, preventing composition and forcing discovery via trial-and-error; (2) descriptions lack WHEN/WHY guidance (when should an agent call semantic_search vs search_bridge?); (3) no error handling guidance (what happens if a project_id is invalid? Can the agent recover?); (4) no pagination parameters on list tools (list_projects, list_sessions); (5) no parameter validation hints (e.g., content_type enum values, or checkpoint name constraints); (6) semantic_search and search_bridge both exist with minimal differentiation in descriptions, risking LLM confusion. Parameter descriptions are terse but present. Risk classifications (READ_ONLY, WRITE, DESTRUCTIVE, REVERSIBLE) are clearly marked, aiding security modeling. Overall: strong foundation, but missing the refinements that separate B-tier from A-tier tool definitions.
Add new content to a Bridge session for storage
Archive a project (soft delete)
Create project state snapshot for backup
Create new Bridge project workspace
Create new session within a project
Delete Bridge content by ID
Generate title for content using Ollama AI
No output schemas documented for any tool. LLMs cannot infer return types, forcing trial-and-error discovery and preventing tool composition. get_project_summary, get_content_full, list_projects, semantic_search and others lack documented field names, types, and nesting structure.
Descriptions lack WHEN/WHY guidance to disambiguate similar tools. search_bridge (full-text) and semantic_search both retrieve content but descriptions don't explain when to use each. LLMs will guess arbitrarily. Same issue with list_projects vs archive_project/restore_project workflow guidance.
| Scored | Grade | Overall | Spec posture | Rubric |
|---|---|---|---|---|
| 2026-09-22 | C | 69 | 2026-07-28+ | v2 |
| 2026-03-09 | F | 30 | - | v1 |
Retrieve full content text by ID
Get project statistics and recent items overview
Get session details with all content
List all Bridge projects with optional archive filter
List all sessions in a project
Generate context summary for a project
Rebuild FAISS search index for semantic search
Restore an archived project
Text search across Bridge content using full-text search
AI-powered semantic search using FAISS vector similarity
Check service health status and latency metrics
Update existing Bridge content
List tools (list_projects, list_sessions) lack pagination parameters (limit, offset, page_size). No indication of result caps or how to retrieve large datasets.
No error handling guidance in any tool descriptions. LLMs don't know what to do if project_id is invalid, session creation fails, or embeddings reindex fails. Per pattern:recovery-guide, error responses should tell the agent what to do next and which errors are retryable.
Parameter descriptions lack validation constraints. content_type in add_bridge_content has no enum or format spec, LLMs will guess at valid values (e.g. 'text' vs 'plaintext' vs 'TEXT'). No format hints for content, title, or checkpoint names.
Destructive tools (delete_bridge_content) lack dry-run or confirmation step guidance. Per pattern:confirmation-request, irreversible operations should support preview or confirmation to prevent accidental data loss.
prepare_bridge_context and generate_title descriptions are vague. 'Generate context summary' doesn't explain structure (is it markdown? JSON? plain text?) or size. 'Generate title using Ollama AI' doesn't explain input constraints or retry behavior if Ollama is unavailable.