About sub-agents-mcp
sub-agents-mcp is an MCP server for running reusable, Markdown-defined coding agents through a selected coding CLI. It is intended for teams or developers who want shared agent definitions and backend settings across MCP clients, with optional session continuity.
Key features
- 01Define reusable agents in Markdown
- 02Delegate reviews, tests, investigations, and docs
- 03Run agents through supported coding CLIs
- 04Share definitions and backend configuration
- 05Continue work across calls with sessions
Use cases
- 01Delegate a code review from an MCP client
- 02Ask an agent to write unit tests
- 03Investigate a software defect
- 04Continue a longer task across calls
MCP support
The server runs configured coding agents and returns their results to the same MCP conversation. It uses an installed and authenticated supported CLI backend.
Configuration
Local server config is the same for every client. Copy it into your client’s MCP config file.
npx -y sub-agents-mcpAGENTS_DIRAbsolute path to the directory containing agent definition files (.md or .txt)AGENT_TYPEType of AI CLI to use: 'cursor', 'claude', 'gemini', 'codex', 'command-code', 'glm', 'kimi', 'grok', 'antigravity', 'opencode', 'mcode', or 'pi'AGENT_PERMISSIONApproval/sandbox level for sub-agents: 'read-only', 'safe-edit' (default), or 'yolo'AGENT_MODELOptional model override applied to every sub-agent execution by this MCP serverAGENT_EFFORTOptional backend-specific reasoning effort or model variant. Supported by codex, claude, command-code, glm, kimi, grok, antigravity, opencode, mcode, and pi.CURSOR_API_KEYSecretAPI key for cursor-agent authentication (used only when AGENT_TYPE=cursor; passed via env, never via CLI args)CLI_API_KEYSecretProvider API key for AGENT_TYPE=glm or kimi (passed to the claude binary via env, never via CLI args). Restart/reconnect the MCP server after changing it.EXECUTION_TIMEOUT_MSAgent execution timeout in milliseconds, as a positive whole number (default: 300000). The server refuses to start on an invalid value such as "5min".SESSION_ENABLEDEnable session management to maintain execution history across agent calls (default: false)SESSION_DIRDirectory path for storing session files (default: .mcp-sessions in current working directory)SESSION_RETENTION_DAYSNumber of days to retain session history before automatic cleanup (default: 1)AGENTS_SETTINGS_PATHPath to CLI settings file/directory. Claude: --settings arg, Cursor: CURSOR_CONFIG_DIR, Codex: CODEX_HOME. GLM/Kimi/Gemini/Grok/Antigravity/OpenCode/Command Code/MiniMax Code/Pi not supported.Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.
Tools
Local servers expose tools only once running on your machine, and the maintainer has not provided a tool list.
Details
From the project READMESub-Agents MCP Server
Run reusable coding agents from any MCP-compatible client.
Write a reviewer, test writer, or investigator in Markdown, then ask your assistant to use it. The MCP server runs that agent with the coding CLI you choose and returns the result to the same conversation.
What You Can Do
- Delegate code review, test writing, investigation, and documentation to focused agents
- Reuse the same agent definitions across MCP clients with one shared backend and model configuration
- Continue the same agent across multiple calls for longer work
Quick Start
You need Node.js 22 or later, an MCP-compatible client, and one supported coding CLI installed and signed in. This example uses Codex.
1. Create an Agent
Create an agents folder anywhere on your machine, then add code-reviewer.md:
# Code Reviewer
Review code for bugs and maintainability issues.
## Task
- Find concrete problems in the requested changes
- Explain why each problem matters
- Point to the affected code
## Done When
- All requested files have been reviewed
- Findings include evidence and suggested next steps
The filename becomes the agent name: code-reviewer.md becomes code-reviewer.
2. Add the MCP Server
Add the server to your client's MCP configuration. Replace AGENTS_DIR with the absolute path to the folder you created.
{
"mcpServers": {
"sub-agents": {
"command": "npx",
"args": ["-y", "sub-agents-mcp"],
"env": {
"AGENTS_DIR": "/absolute/path/to/agents",
"AGENT_TYPE": "codex"
}
}
}
}
Restart or reconnect your MCP client after saving the configuration.
3. Run the Agent
Ask your assistant:
Use the code-reviewer agent to review the authentication changes.
Your assistant runs the agent with Codex and returns the review to the conversation.
Examples
Use the test-writer agent to add unit tests for the auth module.
Use the bug-investigator agent to find the cause of the failed checkout requests.
Use the doc-writer agent to document the public API changes.
Name both the agent and the work you want it to do.
When the MCP Server Fits
Use the MCP server when you want to share the same agents across MCP clients while keeping backend and model configuration in one place.
If you prefer a lighter installation or want each agent to choose its own backend and model, see Sub-Agents Skills.
Supported Backends
Set AGENT_TYPE to the backend you already use:
AGENT_TYPE | Backend | Command |
|---|---|---|
codex | Codex | codex |
claude | Claude Code | claude |
cursor | Cursor CLI | cursor-agent |
command-code | Command Code | command-code |
glm | GLM (Z.ai) | claude |
kimi | Kimi | claude |
grok | Grok Build | grok |
antigravity | Google Antigravity | agy 1.1.12+ |
gemini | Gemini CLI (compatibility) | gemini |
opencode | OpenCode | opencode |
mcode | MiniMax Code | mcode |
pi | Pi | pi |
The selected CLI must be installed and configured before the MCP server starts.
GLM and Kimi require CLI_API_KEY in the MCP server environment. Other backends use the CLI's existing authentication.
For Google models, prefer Antigravity. Gemini CLI remains available for existing enterprise, API key, or Vertex AI configurations.
Shared Agent Settings
Set AGENT_MODEL to use one model for every agent. Omit it to use the backend's default.
AGENT_PERMISSION controls what agents may do:
read-only— review and investigationsafe-edit— edits allowed without approval (default)yolo— unrestricted execution
If an agent reports that an action was blocked, choose a less restrictive mode.
How strictly each level is enforced depends on the backend, so treat it as guidance rather than a security boundary.
Continue Work Across Calls
Set SESSION_ENABLED to "true" when you want an agent to remember earlier calls and continue a longer task. Your assistant must reuse the returned session_id on the next call to continue that session.
If It Does Not Start
- Run the selected backend command directly and confirm that it is installed and signed in
- Make sure
AGENTS_DIRis an absolute path and contains at least one.mdor.txtfile - Restart or reconnect the MCP client after changing its configuration
License
MIT
Comments
New to MCP?
From what the protocol is to installing your first server, these answers cover most first questions.
An open protocol that defines how AI applications connect to external tools and data in a uniform way. Clients talk to the model; MCP servers provide tools, resources and prompt templates. They exchange standard messages, so one server can be reused by many clients.