Show HN: Representing Agents as MCP Servers

https://github.com/lastmile-ai/mcp-agent/tree/main/examples/mcp_agent_server

58•saqadri•11mo ago

Hey HN! A few months ago we shared mcp-agent (https://github.com/lastmile-ai/mcp-agent) [1][2], a lightweight framework that implements every agent pattern from Anthropic’s Building Effective Agents blog [3] and handles MCP server/client management seamlessly. Our core bet is that connecting LLMs to tools, resources, and external systems will soon be MCP-native by default.

Today we're launching a significant update: Agents as MCP servers.

Currently "agentic" behavior exists only on the MCP client side – clients like Claude or Cursor use MCP servers to solve tasks. With this update, Agents can be MCP servers themselves, so that any MCP client can invoke, coordinate and orchestrate agents the same way it does with any other MCP server.

This paradigm shift enables: 1. Agent Composition: Build complex multi-agent systems over the same base protocol (MCP). 2. Platform Independence: Use your agents from any MCP-compatible client 3. Scalability: Run agent workflows on dedicated infrastructure, not just within client environments 4. Customization: Develop your own agent workflows and reuse them across any MCP client.

How an agent server is implemented:

We’ve implemented this in mcp-agent with Workflows. Each workflow is an agent application that can interact with other MCP servers (e.g. summarizing GitHub issues → Slack message). mcp-agent exposes workflows as MCP tools on an MCP Agent Server [5]:

- workflows/list – list available workflows - workflows/{WorkflowName}/run – Execute the workflow (async) - workflows/{WorkflowName}/get_status – Check workflow status - workflows/{WorkflowName}/resume – Resume paused workflow (e.g. with human input) - workflows/{WorkflowName}/cancel – Terminate workflow

We’ve also implemented Temporal for durable execution [6], so agent workflows can be paused, resumed and retried in production settings.

This demo [7] shows Claude invoking an MCP agent server, running workflows when appropriate, and polling for status. It basically shows agentic behavior on both the MCP client and MCP server side.

We're excited about the potential this unlocks—especially as more applications become MCP-compatible clients. We'd love your feedback and ideas!

[1] - https://news.ycombinator.com/item?id=42867050

[2] - https://github.com/lastmile-ai/mcp-agent

[3] - https://www.anthropic.com/research/building-effective-agents

[4] - https://github.com/github/github-mcp-server

[5] - https://github.com/lastmile-ai/mcp-agent/tree/main/examples/...

[6] - https://github.com/lastmile-ai/mcp-agent/tree/main/examples/...

[7] - https://youtu.be/pLe2GAjEoYs [DEMO]

Comments

msamadi•11mo ago

This is a fascinating evolution of the MCP ecosystem. How are you thinking about agent discovery, authentication, and trust in a world where agents are both clients and servers

saqadri•11mo ago

Authentication and authorization is something we are thinking about a lot at the moment, especially for agents that are MCP servers.

Our thoughts here are to handle auth the same way that the MCP spec outlines auth (https://modelcontextprotocol.io/specification/2025-03-26). The key thing is to send authorization requests back to the user in a structured way. For example, if Agent A invokes Agent B, which requires user approval for executing a tool call, that authorization request needs to be piped back to the client, and then propagated back to the agent.

This is technically possible to do with the MCP protocol as it exists today, but I think we will want to add that support in mcp-agent itself so it is easy to pause an agent workflow waiting for authentication/authorization.

One nice property of representing agents as MCP servers is that Agent discovery is the same as server discovery.

yujian•11mo ago

i've used this repo, it's a great starter pack

saqadri•11mo ago

Would love your feedback on the Temporal support and the MCP agent server concept which we merged in yesterday

SlimIon729•11mo ago

That's great to hear! We'd love to know more about your experience and any thoughts you have on it.

Beefin•11mo ago

Super cool direction. Making agents first-class MCP servers feels like a natural next step—especially for scaling multi-agent coordination across infra boundaries. Curious how you’re handling observability at the server level—do you expose structured logs or telemetry for workflows running across agents? This could be huge for debugging large-scale agentic chains.

saqadri•11mo ago

This is exactly what we're working on at the moment! (If you're curious about following along progress, check out feature/distributed_tracing branch -- https://github.com/lastmile-ai/mcp-agent/tree/feature/distri...)

The nice thing about representing agents as MCP servers is we can leverage distributed tracing via OTEL to log multi-agent chains. Within the agent application, mcp-agent tracing follows the LLM semantic conventions from OpenTelemetry (https://opentelemetry.io/docs/specs/semconv/gen-ai/). For any MCP server that the agent uses, we propagate the trace context along.

datadrivenangel•11mo ago

Really cool, but it seems like recursive agents are going to bog down into microservice hell.

scottcha•11mo ago

Yeah, that was my first thought. I actually wrote a blog post a few weeks ago modeling the point at which agent recursion really gets out of control. https://www.neuralwatt.com/blog/agent-bedlam-a-future-of-end...

esafak•11mo ago

Agents should be given a time budget, which they can allot to other agents as they see fit. And it's easy to enforce: you kill the process after the allotted time.

saqadri•11mo ago

Agreed. Time, token, cost budget caps would be a great addition. Will add it as a feature request :)

SlimIon729•11mo ago

That's a valid concern. In `hacker-news-agents`, we're exploring ways to manage the complexity of multi-agent interactions. Perhaps a structured approach to agent communication and state could mitigate some of that 'microservice hell' feel.

saqadri•11mo ago

I think that's a fair point. How I envision this to realistically evolve is that MCP servers will expose workflows that handle common tasks. These workflows will be "agentic" because they'll involve LLMs interacting with tools and data, and it will be facilitated over MCP. For example, it would be great to have a "triage" workflow agent exposed by Linear, which in turn might use some MCP servers to make tool calls etc.

I don't know of a usecase where there are such deep recursive agent chains that it becomes unmanageable.

I almost think of mcp-agents as a modern form of scripting – we have agent workflows (e.g. generating a summary of new GitHub issues and posting on Slack), and exposing them as MCP servers has enabled us to use them in our favorite MCP clients.

max_on_hn•11mo ago

This is super cool! We use a similar approach for CheepCode: our agent process connects to an MCP server that then "drives" the rest of the interaction.

This paradigm feels like the obvious next step for agents. It more closely models human interaction (to the degree that this is desirable) and unlocks a lot of optimizations + powerful functionality.

It is going to be an exciting rest of the year!

3abiton•11mo ago

This a bit confusing, and maybe I am missing a piece of the puzzle, are mcp agents and mcp clients being used interchangeably?

saqadri•11mo ago

This diagram might be helpful: https://pbs.twimg.com/media/GrgGy2jWQAAittE?format=jpg&name=...

Loss of epigenetic information as a cause of mammalian aging

Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

The AI coding tool config problem is getting worse, not better

FDA Clearance of IND Application for ER-100 in Optic Neuropathies

Show HN: Seeker – Career Routing Engine

Evaluating ER-100 for Safety in People with Glaucoma or Optic Nerve Conditions

Tython – Just a Small Language

Artisan (YC W24) uses AI to rip off "This is Fine" artist for ad

The Final Form of Software Development

Deep Dive into the OTel Normalizer groundcover Built for GenAI

MathStudio Android APK modernized for Android >= 7

Unruly Play

I Wrote Ultralearning. This Is What I'd Change Because of AI

Show HN: UIGen – Runtime front end for any OpenAPI spec with AI skills

Turning live heart rate data into a generative audio story

Engaging Essays in Cosmology [1971-2026]

Yann LeCun's Billion Dollar Bet [video]

Show HN: Stay Lean – Calorie Navigation

Making Postman load 60% Faster

Model Engines Manufacturable drawings/plans

I wrote a custom CUDA inference engine to run Qwen3.5-27B on $130 mining cards

Einstein's Big Idea Documentry(2005) - 1h 49M [video]

Pgxbackup: Continuity Support for PgBackRest

Show HN: Keryx: TypeScript framework where one Action becomes HTTP, WS, CLI, MCP

The Reality of Being a Man in Your 50s in South Korea

Mouse Pointer as a Mere Mortal

Quantum Machine Learning: A Pragmatic Guide for Classical ML Engineers

Redesigning Agent Skills – two missing parts

NodeMind – binary document index, 48× smaller than float32 RAG, no GPU required

MX Script: a scripting language for one file web APIs

Loss of epigenetic information as a cause of mammalian aging

Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

The AI coding tool config problem is getting worse, not better

FDA Clearance of IND Application for ER-100 in Optic Neuropathies

Show HN: Seeker – Career Routing Engine

Evaluating ER-100 for Safety in People with Glaucoma or Optic Nerve Conditions

Tython – Just a Small Language

Artisan (YC W24) uses AI to rip off "This is Fine" artist for ad

The Final Form of Software Development

Deep Dive into the OTel Normalizer groundcover Built for GenAI

MathStudio Android APK modernized for Android >= 7

Unruly Play

I Wrote Ultralearning. This Is What I'd Change Because of AI

Show HN: UIGen – Runtime front end for any OpenAPI spec with AI skills

Turning live heart rate data into a generative audio story

Engaging Essays in Cosmology [1971-2026]

Yann LeCun's Billion Dollar Bet [video]

Show HN: Stay Lean – Calorie Navigation

Making Postman load 60% Faster

Model Engines Manufacturable drawings/plans

I wrote a custom CUDA inference engine to run Qwen3.5-27B on $130 mining cards

Einstein's Big Idea Documentry(2005) - 1h 49M [video]

Pgxbackup: Continuity Support for PgBackRest

Show HN: Keryx: TypeScript framework where one Action becomes HTTP, WS, CLI, MCP

The Reality of Being a Man in Your 50s in South Korea

Mouse Pointer as a Mere Mortal

Quantum Machine Learning: A Pragmatic Guide for Classical ML Engineers

Redesigning Agent Skills – two missing parts

NodeMind – binary document index, 48× smaller than float32 RAG, no GPU required

MX Script: a scripting language for one file web APIs

Show HN: Representing Agents as MCP Servers

Comments