mcp-context-cache
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 | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| get_project_contextA | Returns formatted context for a list of files. Use this to load specific files into AI agent context with caching. |
| get_directory_contextB | Recursively packages all files in a directory and returns them as formatted context for AI agents. |
| get_context_from_configA | Reads contextcache.json and returns full project context with module instructions and caching. |
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 3 tools
Each tool has a distinct input source: config file, directory, or specific file list. No overlap in purpose.
All tools use the consistent 'get_<object>_context' pattern, making them predictable and easy to differentiate.
Three tools is well-scoped for a context-caching server, covering the primary ways to load context without unnecessary bloat.
The set covers the main context retrieval methods (config, directory, file list) but lacks cache management or update capabilities, which are minor gaps.