Dedalus MCP Documentation Server
OfficialServer Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_API_KEY | Yes | Your OpenAI API key (required for AI features) |
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": false
} |
| prompts | {
"listChanged": false
} |
| resources | {
"subscribe": false,
"listChanged": false
} |
| experimental | {} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| list_docsA | List all available documentation files Args: directory: Optional subdirectory to list (relative to docs root) Returns: List of document metadata |
| search_docsA | Search documentation using keyword matching (semantic search ready) Args: query: Search query string max_results: Maximum number of results to return search_content: Whether to search in document content search_titles: Whether to search in document titles Returns: List of matching documents with relevance scores |
| ask_docsA | Answer questions about documentation using AI Args: question: The question to answer context_docs: Optional list of document paths to use as context max_context_length: Maximum characters of context to include user_id: Optional user identifier for rate limiting Returns: AI-generated answer with sources |
| index_docsA | Index or re-index all documentation for improved search Args: rebuild: Whether to rebuild the entire index from scratch Returns: Indexing statistics |
| analyze_docsA | Analyze documentation for specific tasks (foundation for agent handoffs) Args: task: Analysis task (e.g., "find_gaps", "generate_outline", "check_consistency") docs: Optional list of specific documents to analyze output_format: Output format (summary, detailed, structured) Returns: Analysis results ready for agent handoff |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| documentation_query | Generate a prompt for querying documentation Args: topic: The topic to query about detail_level: Level of detail (brief, medium, comprehensive) Returns: A formatted prompt for documentation queries |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool has a clearly distinct purpose: analyze performs analysis tasks, ask answers questions, index rebuilds the index, lists files, and search does keyword matching. No overlap in functionality.
All tools follow a consistent verb_noun pattern (e.g., analyze_docs, ask_docs) using snake_case, making naming predictable and clear.
With 5 tools covering the core documentation operations (list, search, ask, analyze, index), the count is well-scoped for a documentation server without being too few or too many.
The tool surface covers major use cases (searching, querying, analyzing, indexing), but lacks a direct 'get_doc' for raw content retrieval and does not support individual document management (add/delete). Minor gaps that agents can work around.