Schema | Context MCP

Context MCP

Describes the environment variables required to run the server.

Name	Required	Description
`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.

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.

Features and capabilities supported by this server

Protocol revision2025-11-25

Capability	Details
`tools`	{}
`resources`	{}

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)

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
`Context Database Statistics`	Current statistics about the context vector database

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/Raunak-dev-18/context-mcp'

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