DawnMCP
OfficialServer 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 |
|---|---|
| tasks | {
"list": {},
"cancel": {},
"requests": {
"tools": {
"call": {}
}
}
} |
| tools | {
"listChanged": true
} |
| prompts | {
"listChanged": true
} |
| resources | {
"subscribe": true,
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| memory_save_memoryA | Save a piece of information to long-term memory. Use this to remember user preferences, project context, technical decisions, conversations, or important events for future reference. |
| memory_search_memoryA | Search stored memories by semantic similarity. Use this to recall past conversations, find previously stored project context, retrieve technical decisions, or look up user preferences. |
| memory_update_memoryA | Update the content of an existing memory. The embedding is regenerated automatically. Use the memory ID from a previous search result. |
| memory_delete_memoryA | Permanently delete a stored memory by its ID. Use the memory ID from a previous search result. |
| repo_analyze_repositoryA | Analyze a local repository to understand its structure, framework, dependencies, and architecture. Scans all files, performs AST parsing on source code, detects patterns, and generates an AI summary. |
| repo_scan_filesC | Scan a local repository and list all files with classified types, languages, and aggregate statistics. |
| repo_index_repositoryA | Index a local repository for semantic code search. Scans files, splits them into function/class chunks, generates embeddings using Ollama, and stores them in ChromaDB. |
| repo_ask_codebaseA | Ask a natural language question about an indexed codebase. Uses RAG (retrieval-augmented generation) over ChromaDB vector search and Qwen2.5-Coder LLM. |
| repo_build_knowledge_graphA | Construct a structural knowledge graph of files, functions, classes, and dependencies for a repository. |
| repo_query_knowledge_graphB | Query the repository knowledge graph by entity name or type (file, function, class, module, dependency). |
| repo_explain_architectureC | Generate a detailed architectural explanation of a repository. |
| repo_explain_projectB | Generate a comprehensive project explanation including architecture, technology stack, and module structure. |
| repo_find_feature_locationB | Locate where a specific feature or capability is implemented in the codebase. |
| repo_impact_analysisA | Analyze potential impact of modifying a specific file or symbol across the codebase. |
| repo_summarize_repositoryC | Get a concise high-level technical summary of the repository. |
| agent_plan_taskB | Decompose a complex software engineering request into structured implementation phases using the PlannerAgent. |
| agent_execute_stepB | Generate production code or step-by-step implementation for a planned step using the ExecutorAgent. |
| agent_review_codeB | Perform a comprehensive code review auditing security, performance, quality, and best practices using the ReviewerAgent. |
| agent_debug_issueA | Diagnose error logs, stack traces, or failing tests to identify root cause and recommended fix using the DebuggerAgent. |
| documents_add_documentA | Store and index a project document, spec, or architecture guide for semantic retrieval. |
| documents_search_documentsA | Search stored project documentation by semantic similarity. |
| documents_list_documentsA | List all stored project documents and specs. |
| documents_delete_documentB | Delete a stored document by its UUID. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
| Memory History | The 50 most recent memories stored by the AI assistant, sorted newest first. |
| User Profile | Stored user preferences and profile information from memory. |
| Project Context | Current project context and key architectural decisions. |
| Available Documents | List of all indexed project documentation and specs. |
| Health Checks | Current health status of all registered health checks |
| Widget Examples | Provides metadata and examples for all registered UI widgets |
TDQS
Scored across 23 tools
Most tools have clearly distinct purposes, but there are close overlaps among repo_explain_architecture, repo_explain_project, and repo_summarize_repository, as well as between repo_analyze_repository and repo_scan_files. Descriptions help, but an agent could confuse these similar-sounding tools.
Names follow a consistent category_verb_noun pattern with underscores (e.g., documents_add_document, memory_search_memory, repo_index_repository). Minor deviations exist in plural/singular forms (search_documents vs add_document) and semantically similar verbs like 'explain' versus 'summarize', but overall the pattern is predictable.
At 23 tools, the set is on the heavier side. The four domains each justify their existence, but the repo category has 11 tools, with several overlapping analysis/explanation options that could be consolidated. Still, it's within a workable range.
Documents and memory have near-complete CRUD coverage (missing document update), and repo tools cover scanning, indexing, analysis, and querying. Agent tools provide plan/execute/review/debug lifecycle. Minor gaps like no repository unindex or knowledge graph deletion, but core workflows are well covered.