Convolut MCP Server
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| CONVOLUT_API_KEY | Yes | Your Convolut API key (format: convolut_sk_...) |
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
Server capabilities have not been inspected yet.
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_contextsC | Search and filter contexts with advanced options including keywords, tags, categories, and date ranges |
| get_contextB | Retrieve a specific context by its ID, including full content and metadata |
| create_contextC | Create a new context with title, content, tags, and metadata |
| update_contextC | Update an existing context with new title, content, tags, or metadata |
| delete_contextC | Delete a context permanently by its ID |
| search_contextsC | Perform semantic search across contexts to find relevant information |
| consolidate_contextsC | Merge multiple contexts using AI to create a consolidated summary or composition |
| plan_from_contextsC | Analyze contexts and generate actionable plans using AI |
| export_contextsC | Export contexts in various formats (JSON, XML, TXT, Markdown) for integration with other systems |
| get_raw_urlA | Generate a temporary raw URL for a context that can be accessed without authentication (expires in 10 minutes) |
| get_context_statsB | Get statistical information about contexts including counts, categories, and usage metrics |
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 11 tools
Every tool has a clearly distinct purpose with no ambiguity. For example, create_context, get_context, update_context, and delete_context form distinct CRUD operations, while consolidate_contexts, plan_from_contexts, and search_contexts each serve unique AI-driven functions. The descriptions clearly differentiate overlapping tools like list_contexts (filtering) and search_contexts (semantic search).
All tool names follow a consistent verb_noun pattern using snake_case, such as create_context, delete_context, and get_context_stats. There are no deviations in naming conventions, making the set predictable and readable. This uniformity aids in agent selection and understanding of tool purposes.
With 11 tools, the count is well-scoped for a context management server, covering core operations without bloat. Each tool earns its place by addressing specific needs like CRUD, search, export, and AI analysis. This aligns with typical server scopes of 3-15 tools, ensuring comprehensive coverage without overwhelming complexity.
The tool surface provides complete CRUD/lifecycle coverage for context management, including create, get, update, delete, list, and search. It extends beyond basics with AI features (consolidate, plan), utilities (export, raw URL), and analytics (stats), leaving no obvious gaps. Agents can perform end-to-end workflows without dead ends.