agents-md-generator
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| AGENTS_MD_LOG_LEVEL | No | Server log verbosity. Set to DEBUG to see per-file analysis details. Valid values: DEBUG, INFO, WARNING, ERROR | INFO |
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 |
|---|---|
| scan_codebaseA | Scan and analyze a codebase with tree-sitter, producing a structured context payload. Performs AST analysis, change detection, and caching. Writes the analysis payload to disk and returns instructions to retrieve it via read_payload_chunk. The payload contains pure architectural data — no AGENTS.md writing instructions. Use this tool when you need deep codebase understanding for any task (code review, refactoring, planning, Q&A). To generate or update AGENTS.md specifically, use generate_agents_md instead — it orchestrates the full workflow automatically. Supported languages: Python, C#, TypeScript, JavaScript, Go. Args: params (ScanCodebaseInput): Input parameters containing: - project_path (str): Path to the project root (default: ".") - force_full_scan (bool): Ignore cache and rescan everything (default: False). Returns: str: JSON with total_chunks and instructions to call read_payload_chunk. |
| read_payload_chunkA | Read a chunk of the analysis payload produced by scan_codebase. Call this tool repeatedly starting at chunk_index=0, incrementing by 1 each time, until the response contains has_more=false. Concatenate all 'data' fields in order to reconstruct the full payload JSON. The payload file is automatically deleted after the last chunk is read. Args: params (ReadPayloadChunkInput): Input parameters containing: - project_path (str): Path to the project root (must match scan_codebase call). - chunk_index (int): Zero-based index of the chunk to retrieve. Returns: str: JSON with fields: chunk_index, total_chunks, has_more (bool), data (str). On the last chunk (has_more=false), the payload file is deleted from disk. |
| generate_agents_mdA | Orchestrate the full AGENTS.md creation or update workflow. Determines whether to create or update AGENTS.md by checking if the file already exists. Returns writing rules, the existing content (if any), and step-by-step instructions to scan the codebase and produce the final file. Use this tool whenever the user asks to generate, create, update, or refresh AGENTS.md. For general codebase context without AGENTS.md generation, use scan_codebase + read_payload_chunk directly. Args: params (GenerateAgentsMdInput): Input parameters containing: - project_path (str): Path to the project root (default: ".") Returns: str: JSON with agents_md_path, agents_md_rules, existing_agents_md (if any), and step-by-step instructions for the agent to follow. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
| initialize-agents-md | Guide the agent to create the first AGENTS.md file for a project. |
| update-agents-md | Guide the agent to update an existing AGENTS.md after code changes. |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 3 tools
The three tools have distinct roles: scan_codebase produces the payload, read_payload_chunk retrieves it, and generate_agents_md orchestrates. scan_codebase and generate_agents_md could initially look similar since both relate to codebase analysis, but the descriptions explicitly delineate when to use each, resolving the ambiguity well.
All names use snake_case with a verb-first convention (scan_codebase, generate_agents_md, read_payload_chunk), which is predictable and readable. read_payload_chunk adds an extra noun qualifier relative to the others, a minor deviation from a strict verb_noun pattern.
Three tools is slightly thin, but each earns its place in a narrow, well-defined workflow (scan → read → generate). There is no obvious redundancy, and the count matches the focused purpose of AGENTS.md generation.
The surface covers the full generation lifecycle: scanning with cache control, chunked payload retrieval, and a create-or-update orchestrator that also feeds the writing rules. Minor gaps exist (no explicit validation or standalone cache-management tool), but agents can complete the core workflow.