mcpField
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Deploy to Agents

Deploy to Agents

Remote
deploytoagents.comBusiness & Marketing0Updated 14w ago

About Deploy to Agents

Deploy to Agents audits public surfaces used to discover and recommend agents, then produces evidence-backed distribution plans. It is for organizations assessing how their offerings appear to agents; it also provides a remote MCP server, clients, and an agent-first CLI.

Key features

  1. 01Audit public agent-facing surfaces
  2. 02Return evidence receipts
  3. 03Create prioritized distribution plans
  4. 04Record discovery observations
  5. 05Provide JSON-oriented CLI commands

Use cases

  1. 01Assessing how a product appears on agent-facing surfaces
  2. 02Collecting evidence from discovery observations
  3. 03Planning technical and external-authority distribution work

MCP support

The remote MCP server is available at `https://deploytoagents.com/mcp` and exposes `audit_app`, `get_audit_result`, `create_distribution_plan`, and `get_customer_zero_evidence` tools.

Configuration

Remote servers need no local install. Pick your client, then copy the config or install in one click.

Endpointhttps://deploytoagents.com/mcp
Copy install command
Claude CodeTerminal
Cursor.cursor/mcp.json
VS Code.vscode/mcp.json
Claude Desktopclaude_desktop_config.json
Windsurf~/.codeium/windsurf/mcp_config.json

Run commands in a terminal; paste JSON into the client’s MCP config and restart. Servers that need sign-in will prompt on first connect.

Tools

4
ParameterTypeRequiredDescription
urlstringYesPublic website or application URL to audit

Details

From the project README

Deploy to Agents SDK

Public JavaScript client and registry metadata for the Deploy to Agents remote MCP server.

The remote server is published in the official MCP Registry as com.deploytoagents/server and is served from https://deploytoagents.com/mcp. The JavaScript client and authenticated agent-first CLI are published as [email protected] on npm, with an equivalent deploytoagents==0.1.1 client on PyPI.

Agent-first CLI

npx deploytoagents login
npx deploytoagents whoami
npx deploytoagents portfolio --json
npx deploytoagents discovery --json
npx deploytoagents discovery-record --input observation.json --json
npx deploytoagents audit https://example.com --json

The package installs both deploytoagents and the shorter d2a command. Google login uses Authorization Code with PKCE and a temporary loopback callback. On Windows the refresh credential is encrypted for the current OS user with DPAPI; CI can provide a short-lived identity token through DEPLOYTOAGENTS_TOKEN. Discovery Lab can be read or supplied with a JSON observation file (or stdin via --input -). All command results and errors have stable JSON forms for agent use.

{
  "hostname": "example.com",
  "surface": "claude",
  "model": "model label shown by the surface",
  "prompt": "Exact generic, unbranded prompt",
  "outcome": "not-mentioned",
  "freshSession": true,
  "responseExcerpt": "Optional relevant excerpt",
  "citations": ["https://example.org/source"]
}

Valid outcomes are recommended, mentioned, not-mentioned, and error. The server verifies that the signed-in organization owns the target hostname.

Deploy to Agents currently audits public agent-facing surfaces, returns unlisted evidence receipts, and creates prioritized technical and external-authority distribution plans. It does not yet claim to publish every customer artifact or guarantee recommendation by any model.

Connect directly through MCP

Use this Streamable HTTP endpoint in any compatible MCP client:

https://deploytoagents.com/mcp

Available tools:

  • audit_app
  • get_audit_result
  • create_distribution_plan
  • get_customer_zero_evidence

JavaScript client

npm install deploytoagents
import { DeployToAgentsClient } from "deploytoagents";

const client = new DeployToAgentsClient();

try {
  const queued = await client.auditApp("https://example.com");
  console.log(queued.receipt_url);

  const result = await client.getAuditResult(queued.audit_id);
  if (result.status === "completed") {
    console.log(await client.createDistributionPlan(queued.audit_id));
  }
} finally {
  await client.close();
}

Python client

pip install deploytoagents
from deploytoagents import DeployToAgentsClient

async with DeployToAgentsClient() as client:
    queued = await client.audit_app("https://example.com")
    print(queued["receipt_url"])

Customer Zero

Deploy to Agents uses its own system as its first customer. The current 100/100 receipt verifies technical surfaces only. Independent, unbranded discovery remains explicitly not-yet-proven.

Development

npm install
npm test
npm run smoke

Evidence policy

This project distinguishes owned evidence, externally verified artifacts, and independent recommendations. It does not create fake testimonials, automated community posts, coordinated votes, or links intended primarily to manipulate rankings.

License

MIT

Comments

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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.