agent-as-mcp-tool

A tutorial for making an AI agent available as a tool through MCP, an open standard that lets compatible programs call tools.

In plain words
What is it for?
Use it to wrap a C# agent as a callable tool, register it with an MCP server, and let other supported clients use it.
Why use it?
It shows how other MCP-compatible systems can invoke the agent instead of keeping it available only inside one application.

Agent for Codex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add agents/managedcode/dotpilot/agent-as-mcp-tool
Clone the repo
git clone --depth 1 https://github.com/managedcode/dotPilot

Made for: Codex.

Per session 13 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,139 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 100% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00013 $0.01139
Opus 5 $0.00006 $0.00570
Sonnet 5 $0.00003 $0.00228
Haiku 4.5 $0.00001 $0.00114

Measured 2d ago against content hash 742fd4dd6d71, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

agent-as-mcp-tool scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

100% identical to agent-as-mcp-tool — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

.codex/skills/dotnet-microsoft-agent-framework/references/official-docs/tutorials/agents/agent-as-mcp-tool.md · 156 lines

How it starts

The opening of the file, as written. The whole thing — 156 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Expose an agent as an MCP tool

::: zone pivot="programming-language-csharp"

This tutorial shows you how to expose an agent as a tool over the Model Context Protocol (MCP), so it can be used by other systems that support MCP tools.

Prerequisites

For prerequisites see the Create and run a simple agent step in this tutorial.

Install NuGet packages

To use Microsoft Agent Framework with Azure OpenAI, you need to install the following NuGet packages:

dotnet add package Azure.AI.OpenAI --prerelease
dotnet add package Azure.Identity
dotnet add package Microsoft.Agents.AI.OpenAI --prerelease

To also add support for hosting a tool over the Model Context Protocol (MCP), add the following NuGet packages

dotnet add package Microsoft.Extensions.Hosting --prerelease
dotnet add package ModelContextProtocol --prerelease

Expose an agent as an MCP tool

You can expose an AIAgent as an MCP tool by wrapping it in a function and using McpServerTool. You then need to register it with an MCP server. This allows the agent to be invoked as a tool by any MCP-compatible client.

First, create an agent that you'll expose as an MCP tool.

using System;
using Azure.AI.OpenAI;
using Azure.Identity;
using Microsoft.Agents.AI;
using OpenAI;

AIAgent agent = new AzureOpenAIClient(
    new Uri("https://<myresource>.openai.azure.com"),
    new AzureCliCredential())
        .GetChatClient("gpt-4o-mini")
        .AsAIAgent(instructions: "You are good at telling jokes.", name: "Joker");

Turn the agent into a function tool and then an MCP tool. The agent name and description will be used as the mcp tool name and description.

using ModelContextProtocol.Server;

McpServerTool tool = McpServerTool.Create(agent.AsAIFunction());

Setup the MCP server to listen for incoming requests over standard input/output and expose the MCP tool:

using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Hosting;
using ModelContextProtocol.Server;

HostApplicationBuilder builder = Host.CreateEmptyApplicationBuilder(settings: null);
builder.Services
    .AddMcpServer()
    .WithStdioServerTransport()
    .WithTools([tool]);

await builder.Build().RunAsync();

Read the full file on GitHub · 156 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2d ago First seen · 156 lines · 13 tokens per session scan A 742fd4dd6d71

Subscribe to this mod's changes

agent-as-mcp-tool is an agent published in the GitHub repository managedcode/dotPilot (23 stars, last pushed 4mo ago), licensed MIT. It adds 13 tokens to every session and 1,139 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to agent-as-mcp-tool, differing in 0 lines, and is treated as a copy.

Related

Other agents, from other repositories

knowledge-ops

Executes knowledge management operations under CKO direction. Audits consistency, distributes learnings, optimizes memory files, and detects knowledge gaps across the agent fleet.

RD-DCS/venutian-antfarm · 36 tokens

Explore

Fast read-only codebase & docs exploration. Returns structured findings, never raw file dumps.

BlackBeltTechnology/pi-agent-dashboard · 18 tokens

external-system-integration-expert

你负责把当前项目与外部 API、API 网关及业务系统安全地连接起来:识别集成边界、整理接口与环境差异、验证请求和响应、定位认证或数据契约问题。.

agents-universe/agents-universe · 33 tokens

Audit

Deep security + performance audit of a specific diff. Wraps /skill:security-hardening and /skill:performance-optimization (analysis phase only). Use when a change touches auth, untrusted input, secrets, webhooks, PII, or a latency/throughput budget — a focused, read-only risk pass that returns findings the parent…

BlackBeltTechnology/pi-agent-dashboard · 98 tokens

registry

InitRunner's role registry lets you install, share, and discover roles from InitHub and OCI registries. Roles are downloaded, validated, and saved to /.initrunner/roles/ where they integrate automatically with the CLI.

vladkesler/initrunner · 0 tokens

role_generation

InitRunner provides a single initrunner new command for creating role.yaml files. It supports multiple seed modes (templates, AI generation, examples, hub bundles, or local files) and an interactive refinement loop for iterating on the YAML before saving. Run with no arguments in a terminal and it shows a guided start…

vladkesler/initrunner · 0 tokens