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Clarify hybrid semantic + full-text search in MCP descriptions

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Agents were misreading kb_search as keyword-only because the vector/semantic
component was only mentioned in the negative ("fts_only: no vector similarity").
Lead with hybrid semantic + BM25 + RRF in the server instructions, kb_search
docstring, and MCP.md so agents recognise it as a vector search tool.
This commit is contained in:
Steve Cliff
2026-05-15 18:19:42 +01:00
parent 9eccc527ae
commit e6e91f1d5c
2 changed files with 26 additions and 12 deletions
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MCP.md
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@@ -1,6 +1,6 @@
# MCP Server (Agent Integration)
The MCP server exposes kb operations as native MCP tools, so agents can search, add notes, upload files, and manage documents without shelling out to the CLI.
The MCP server exposes kb operations as native MCP tools, so agents can search, add notes, upload files, and manage documents without shelling out to the CLI. `kb_search` is hybrid: dense vector embeddings (semantic similarity) fused with BM25 full-text ranking via Reciprocal Rank Fusion, so agents can ask natural-language questions and find conceptually related content even when the exact words don't match.
## Start the MCP server
@@ -27,7 +27,7 @@ docker run -d --name kb-mcp \
| Tool | Description |
|---|---|
| `kb_search` | Hybrid search with optional tag/type filters |
| `kb_search` | Hybrid semantic (vector) + full-text search with tag/type filters |
| `kb_addnote` | Add a text note (queued for async ingestion) |
| `kb_update_note` | Update an existing note in place |
| `kb_get` | Get document details by ID or source path |