Agentomy MCP Gateway

Agentomy MCP Gateway

Governs any stdio MCP server by interposing between the agent and the server, enforcing policy on every tools/call and refusing denied actions before they reach the upstream server.

Category
Visit Server

README

Agentomy MCP Gateway

Governs any stdio MCP server by sitting between the agent and the server. Every tools/call is checked against your policy before it reaches the server. A refusal is answered by the gateway and never forwarded, so the side effect does not happen.

Nothing about the upstream server changes. It is not patched, not forked, and never learns it is being governed.

Why interpose instead of observe

A sidecar that watches MCP traffic and reports on it produces a record of the things it failed to stop. Sitting on the wire is what turns a report into a refusal.

Install and run

# Instead of launching the MCP server directly:
#   my-mcp-server --flag
# launch it through the gateway:
AGENTOMY_ENDPOINT=https://your-agentomy \
AGENTOMY_API_KEY=... \
  agentomy-mcp-gateway -- my-mcp-server --flag

In an agent's MCP configuration, replace the server's command and args:

{
  "mcpServers": {
    "dev-tools": {
      "command": "agentomy-mcp-gateway",
      "args": ["--", "the-original-command", "--its", "--flags"],
      "env": { "AGENTOMY_ENDPOINT": "https://your-agentomy", "AGENTOMY_API_KEY": "..." }
    }
  }
}

That is the whole integration. One config change, per agent, by the operator.

Variable Required Meaning
AGENTOMY_ENDPOINT yes Platform base URL
AGENTOMY_API_KEY no Bearer token
AGENTOMY_AGENT_ID no Identity on the decision, default mcp-gateway
AGENTOMY_TIMEOUT_MS no Decision timeout, default 5000

What it does to the protocol

Message Behaviour
tools/call, permitted Forwarded unchanged
tools/call, refused Not forwarded. JSON-RPC error -32000 on the same id, with data.governed = true and the reason
tools/call, refused, no id Dropped. A notification must never be answered, so the call is stopped and the reply withheld
Everything else Forwarded unchanged
Upstream to agent Forwarded verbatim. Results are not rewritten

Requests are adjudicated in arrival order. Deciding concurrently would let a later call reach the server before an earlier one was resolved, which is a reordering bug that only shows up under load.

Fail-closed, and what that costs you

Every failure path denies:

Condition Reason returned
Endpoint unreachable governance_unreachable
Decision timed out governance_timeout
Non-2xx response governance_http_error
Body not JSON, or no boolean authorized field governance_malformed_response
Fleet halted agent_halted
Policy refused policy_denied

The honest trade: if the platform is down, governed tools stop working. That is the correct behaviour for a governance component and it is a real availability coupling. Run the platform accordingly.

The reasons are distinct on purpose. An operator seeing governance_unreachable has an outage; one seeing policy_denied has a policy question. Collapsing them into "denied" would make the two indistinguishable at exactly the moment the difference matters.

A missing authorized field denies rather than being read for truthiness, because a truthiness check turns any unexpected payload, including an error object, into an allow.

What it does not do

It governs actions, not discovery. tools/list passes through. Narrowing what an agent may see while leaving what it may do ungoverned would be theatre in the wrong place.

It does not rewrite results. The gateway adjudicates requests; making it edit responses would turn it into a participant in the conversation rather than a gate on it.

It does not inspect arguments semantically. Policy receives the tool name and the argument keys, not the values. Argument-level policy is a platform concern and sending full argument values to a decision endpoint would put file contents and shell commands into a second system.

Licence

Apache-2.0.

Recommended Servers

playwright-mcp

playwright-mcp

A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.

Official
Featured
TypeScript
Magic Component Platform (MCP)

Magic Component Platform (MCP)

An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.

Official
Featured
Local
TypeScript
Audiense Insights MCP Server

Audiense Insights MCP Server

Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.

Official
Featured
Local
TypeScript
VeyraX MCP

VeyraX MCP

Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.

Official
Featured
Local
graphlit-mcp-server

graphlit-mcp-server

The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.

Official
Featured
TypeScript
Kagi MCP Server

Kagi MCP Server

An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.

Official
Featured
Python
Neon Database

Neon Database

MCP server for interacting with Neon Management API and databases

Official
Featured
E2B

E2B

Using MCP to run code via e2b.

Official
Featured
Exa Search

Exa Search

A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.

Official
Featured
Qdrant Server

Qdrant Server

This repository is an example of how to create a MCP server for Qdrant, a vector search engine.

Official
Featured