Context MCP
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| GOOGLE_AI_API_KEY | Yes | Your Google AI API key used for generating embeddings (e.g., text-embedding-004). | |
| UPSTASH_VECTOR_REST_URL | Yes | The REST URL for your Upstash Vector Index. | |
| UPSTASH_VECTOR_REST_TOKEN | Yes | The REST Token for your Upstash Vector Index. |
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 | {} |
| resources | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| add_contextB | Add a piece of context/knowledge to the vector database. Use this to store information that can be retrieved later for relevant queries. |
| add_contexts_batchA | Add multiple context entries to the vector database in a single operation. More efficient for bulk indexing. |
| query_contextB | Search for relevant context based on a natural language query. Returns the most semantically similar stored contexts. |
| delete_contextC | Delete a specific context entry by its ID |
| delete_contexts_batchC | Delete multiple context entries by their IDs |
| get_statsB | Get statistics about the vector database (number of stored contexts, dimensions) |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Context Database Statistics | Current statistics about the context vector database |
TDQS
Scored across 6 tools
Every tool has a clearly distinct purpose with no ambiguity. Tools are clearly separated into categories: adding context (single vs. batch), deleting context (single vs. batch), querying context, and getting statistics. The descriptions make it immediately clear which tool to use for each operation.
Tool names follow a perfectly consistent verb_noun pattern throughout. All tools use snake_case with clear action prefixes (add, delete, get, query) followed by the object (context/stats). Even batch operations maintain the same pattern with '_batch' suffix for consistency.
Six tools is well-scoped for a context management server. Each tool earns its place by covering essential operations: CRUD operations (create, read, delete) with both single and batch variants, plus query and statistics capabilities. No tool feels redundant or missing for the domain.
The tool surface provides complete CRUD/lifecycle coverage for context management. It covers creation (add single/batch), retrieval (query), deletion (delete single/batch), and monitoring (stats). There are no dead ends or obvious gaps for the stated purpose of managing a vector database of context/knowledge.