Vectorize MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| semantic_searchA | Search the knowledge base using semantic similarity. This finds content based on meaning, not just keywords. Perfect for finding relevant information even when the exact words don't match. |
| intelligent_answerA | Get an AI-synthesized answer to your question using semantic search. The server searches the knowledge base and uses Claude to generate a natural, direct answer to your question. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 2 tools
The two tools have clearly distinct purposes: one returns a synthesized answer using AI, the other returns raw search results by semantic similarity. No overlap or confusion possible.
Both tool names follow a consistent adjective_noun pattern using snake_case, making them predictable and coherent.
With only 2 tools, the server feels minimal for a knowledge base. While it covers query and Q&A, it lacks the breadth expected (e.g., CRUD), but the count is not extreme.
The server provides only read/query operations, missing essential write capabilities like adding, updating, or deleting documents. This is a significant gap for a knowledge base server.