mcp-delegate
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| DELEGATE_MODEL | Yes | The model to use for delegation. | |
| DELEGATE_API_KEY | No | API key for the endpoint, if required. | |
| DELEGATE_BASE_URL | No | The base URL of the OpenAI-compatible endpoint (e.g., Ollama, OpenRouter). | |
| DELEGATE_MAX_CONCURRENCY | No | Maximum number of concurrent delegations across both tools and any backend. | 4 |
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 |
|---|---|
| delegate_taskA | Delegate a single-shot task to a configured OpenAI-compatible model (e.g. local Ollama or OpenRouter) and return its text response verbatim. Args:
prompt: The task/question to send to the delegated model.
model: Override just the model string for this call.
system_prompt: Optional system prompt to steer the delegated model.
backend: Named backend from models.json (base_url/model/api_key) to
use instead of the default DELEGATE_* env vars. |
| delegate_agentic_taskA | Delegate a multi-step task to a model with its own tool-use loop (read_file, write_file, run_bash) scoped to working_dir. Runs until the model stops calling tools, hits max_iterations, or exceeds timeout_seconds. Returns only the final answer, not the full transcript. The delegated model gets unattended file/bash access within working_dir for the duration of the call - point it at a directory you're comfortable it can read, write, and execute commands in. Args:
task: The task instruction to give the delegated model.
working_dir: Directory the model's tools are scoped to.
model: Override just the model string for this call.
max_iterations: Stop after this many tool-call rounds.
timeout_seconds: Wall-clock budget for the whole task.
backend: Named backend from models.json (base_url/model/api_key) to
use instead of the default DELEGATE_* env vars. |
| list_recent_delegationsA | List the most recent delegate_task / delegate_agentic_task calls (backend, model, task, duration, iterations, success, token usage, USD cost if the model has a pricing.json entry, truncated result), most recent first. Answers "what did the delegated model actually do" without re-running anything. Args: limit: Max number of records to return (default 20). |
| get_delegation_transcriptA | Full message transcript (every model message and tool call/result) for one delegation, if it was run with capture_transcript=True. Get the id from list_recent_delegations. Returns an error string if no transcript was captured for that id. Args:
delegation_id: The |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
MCP directory API
We provide all the information about MCP servers via our MCP API.
curl -X GET 'https://glama.ai/api/mcp/v1/servers/hessenpepper/mcp-delegate'
If you have feedback or need assistance with the MCP directory API, please join our Discord server