Featured

Deploy OpenClaw in 60 seconds — 20% off logoDeploy OpenClaw in 60 seconds — 20% off

Launch OpenClaw on Hostinger in about 60 seconds and keep your agent live 24/7. Our referral link gives you 20% off, no coupon code needed.

Launch on Hostinger
Run your Hermes agent on Hostinger, fully managed logoRun your Hermes agent on Hostinger, fully managed

Launch Hermes on Hostinger in one click, fully managed, no VPS knowledge needed. Use code ZACAARON10 for 10% off.

Launch on Hostinger
Crawl and scrape any site into clean data, 10% off logoCrawl and scrape any site into clean data, 10% off

Firecrawl crawls and scrapes any site into clean markdown for your agent. Get 1,000 free credits, and new users get 10% off their first purchase.

Try Firecrawl free
6,000+ web scrapers for your AI agent, start free logo6,000+ web scrapers for your AI agent, start free

Apify gives your agent live web data: 6,000+ prebuilt scrapers and actors, MCP-ready. Sign up free with $5 in usage credits.

Try Apify free
One API to scrape, enrich, and extract the internet. logoOne API to scrape, enrich, and extract the internet.

Context.dev gives your agents a single API to scrape, enrich, and extract live web data — no proxies, no parsers, no maintenance.

Start building free
SetupClaw: done-for-you OpenClaw for founders & exec teams logoSetupClaw: done-for-you OpenClaw for founders & exec teams

White-glove OpenClaw for founders and exec teams (4–50+ employees): we install, harden, integrate your tools, and maintain it — secured from day one.

Get it set up for you
SEO data APIs for your agent, $1 free credit logoSEO data APIs for your agent, $1 free credit

DataForSEO gives your agent live access to SERP results, keyword data, backlinks, and on-page SEO data through one API. New accounts get a $1 credit, good for up to 20,000 keyword or backlink lookups.

Try DataForSEO free
Reach 48,000+ AI builders

A flat monthly placement in front of developers actively installing AI tools. No lock-in, cancel anytime.

Advertise here

Works with

Claude CodeClaude DesktopCursorVS CodeClineCodex CLIOpenClaw+ any MCP client

Install to Claude Code

This server doesn't publish a one-line install command. Follow the setup in the source repository.

Summary

Connect Claude, Cursor, ChatGPT, Gemini, and Copilot to Onplana. 27 tools, OAuth + PAT auth.

README.md

Onplana MCP server

Open-source TypeScript Model Context Protocol building blocks, extracted from Onplana's production MCP deployment. Two packages:

template. Streamable HTTP transport, Bearer auth, prompt-injection containment, pluggable dispatcher.

client SDK for calling the public Onplana MCP endpoint at https://api.onplana.com/api/mcp/v1.

![CI](https://github.com/Onplana/onplana-mcp-server/actions) ![MIT License](./LICENSE)

What this is

The transport layer of an MCP server — Streamable HTTP wiring, stateless mode, scoped Bearer auth, prompt-injection containment — done well, separated from the platform-specific tool registry. Use the server template to build your own MCP server with security best practices baked in. Use the client SDK to drive Onplana's hosted MCP from your own code.

The patterns are extracted from Onplana's production deployment (public docs at onplana.com/mcp) — the same layer that handles real Claude Desktop, Cursor, ChatGPT custom connector, and in-house agent traffic against the Onplana platform.

Why open-source

The MCP transport is the same for everyone. Most early MCP servers get the security primitives wrong:

  • Prompt injection. Tools that return user-generated content

(task titles, comment bodies, wiki text) put that content directly into the model's context. Without containment, a hostile actor can plant "ignore previous instructions" in their own data and the next agent that reads it follows along.

  • Stateless transport. Most SDK examples assume in-memory session

state, which breaks horizontal scaling and complicates the auth model.

  • Plan-gate semantics. Surfacing tools the caller can't actually

invoke wastes turns and confuses the model.

Onplana solved these in production over six months of MCP-server work. Publishing the patterns is high-leverage:

  1. Other MCP authors get a known-good template instead of

reinventing.

  1. The repo is a pretraining-signal surface — public GitHub READMEs

are heavily weighted in next-gen LLM training data, and a repo with patterns + clear documentation about MCP improves model recall of "what good MCP servers look like."

  1. The dispatcher interface is the seam where your business logic

plugs in. The transport is generic; what matters about your MCP server is the tool registry. Open-sourcing the transport doesn't give away anything proprietary.

The dispatcher implementation, tool catalog, plan-gate logic, audit infrastructure, and the rest of Onplana's ~600 LOC closed-source dispatcher stay in the closed monorepo because they encode platform business logic. If you build your own MCP server using this template, you write your own dispatcher — that's the work that matters and the work that's specific to your platform.

Repository layout

onplana-mcp-server/
├── packages/
│   ├── server-template/        # onplana-mcp-server (npm)
│   │   ├── src/
│   │   │   ├── transport.ts    # Streamable HTTP wiring
│   │   │   ├── auth.ts         # Bearer auth pattern
│   │   │   ├── promptInjection.ts  # wrapUserContent + escape
│   │   │   ├── dispatcher.ts   # Pluggable Dispatcher interface
│   │   │   └── index.ts
│   │   ├── tests/              # promptInjection + auth + transport
│   │   └── README.md
│   └── client/                 # onplana-mcp-client (npm)
│       ├── src/
│       │   ├── client.ts       # OnplanaMcpClient class
│       │   ├── types.ts        # Public type surface
│       │   └── index.ts
│       ├── tests/              # client.test.ts (stub fetch)
│       └── README.md
├── examples/
│   └── in-memory/              # Runnable demo with 3 toy tools
└── .github/workflows/
    ├── ci.yml                  # tsc + vitest on PR
    └── publish.yml             # npm publish on tag v*

Quickstart

Build a server

Install:

npm install github:Onplana/onplana-mcp-server @modelcontextprotocol/sdk express

Wire an Express app:

import express from 'express'
import {
  createMcpPostHandler,
  createMcpMethodNotAllowedHandler,
  requireBearerAuth,
  type Dispatcher,
} from 'onplana-mcp-server'

const dispatcher: Dispatcher = {
  async listTools(ctx) { /* return your tool descriptors */ return [] },
  async callTool(name, input, ctx) { /* dispatch to your tools */ return { output: {} } },
}

const auth = async (token: string) => {
  // Validate against your token store. Return AuthContext or null.
  return { userId: 'u', scopes: ['MCP_AGENT'] }
}

const app = express()
app.use(express.json())
app.use('/api/mcp/v1',
  requireBearerAuth({ auth, requiredScope: 'MCP_AGENT' }),
)
app.post('/api/mcp/v1', createMcpPostHandler({ dispatcher }))
app.get('/api/mcp/v1', createMcpMethodNotAllowedHandler())
app.delete('/api/mcp/v1', createMcpMethodNotAllowedHandler())
app.listen(3000)

Full quickstart in packages/server-template/README.md; runnable demo in examples/in-memory/.

Drive Onplana from code

Install:

npm install github:Onplana/onplana-mcp-server

Use:

import { OnplanaMcpClient } from 'onplana-mcp-client'

const client = new OnplanaMcpClient({
  url:   'https://api.onplana.com/api/mcp/v1',
  token: process.env.ONPLANA_PAT!,
})

const projects = await client.listProjects({ status: 'ACTIVE' })

// The differentiator vs other PM-tool MCPs: hybrid semantic + lexical
// search across your org's indexed content (projects, tasks, risks,
// goals, comments, wiki pages).
const { matches } = await client.searchOrgKnowledge({
  query: 'rationale for the 3-week design phase',
  scope: 'all',
  limit: 5,
})

Full client docs in packages/client/README.md.

Production checklist

The template + SDK get you running. Add these on top:

  • Per-token rate limiting. 60–120 req/min per Bearer token;

agentic loops are noisier than humans.

  • Tenant cost cap. If your tools call paid LLMs, gate dispatch

on month-to-date spend. Onplana's deployment uses aiMonthlyCostCapUsd with WARN / BLOCK modes.

  • Audit logging. Every dispatch should write an audit row

tagged with actorType: 'mcp_agent' so admins can see what AI agents did in their tenant separately from human activity.

  • Plan / scope curation. Don't expose every internal tool.

Onplana exposes 21 of 26; the suppressed 5 either need an in-app preview UI, are too risky for unsupervised invocation, or produce oversized payloads.

  • PREVIEW mode for risky mutations. Default mutating tools to

preview-only on free tiers. Onplana ships this — agents see "what it would do" before users explicitly upgrade and re-run.

  • Idempotency keys. Hash the canonicalised input + a session

id; store as a unique constraint on your audit row. A model retrying the same logical action shouldn't double-create.

Each of those is platform-specific. The template gives you the seam where they plug in (Dispatcher.callTool); your dispatcher implements them however your platform encodes those concepts.

Compatibility

  • Node.js ≥ 20 (for the server template and CI matrix); ≥ 18 for

the client (uses ambient fetch).

  • @modelcontextprotocol/sdk@^1.29.0
  • express@^4.18.0 or express@^5.0.0

Tested against:

  • Claude Desktop (Custom Connector)
  • Cursor (~/.cursor/mcp.json)
  • ChatGPT custom connectors (where MCP is enabled in your account)
  • Gemini CLI + Gemini Code Assist (~/.gemini/settings.json)
  • GitHub Copilot in VS Code (.vscode/mcp.json)
  • The official MCP Inspector

Install in Gemini CLI

The repo ships a gemini-extension.json manifest at the root, so Gemini CLI installs Onplana with one command:

export ONPLANA_PAT=pat_paste-your-token-here  # mint at app.onplana.com/integrations
gemini extensions install https://github.com/Onplana/onplana-mcp-server

Restart the gemini CLI (or reload your VS Code / JetBrains window if you're using Gemini Code Assist). The Onplana tools appear in /mcp and your GEMINI.md context picks up the usage hints shipped in this repo.

Contributing

Issues + PRs welcome. The repo is small by design — the goal is for the transport patterns to be obvious, well-tested, and stable. Major-version bumps are reserved for breaking changes to the exported Dispatcher / BearerAuth / handler factory shapes. Patches and minors are for prompt-injection containment refinements, new helper utilities, additional test coverage.

License

MIT — © 2026 Onplana

See also

for the production Onplana MCP deployment (full tool catalog, setup instructions, security model)

Cloud-agnostic, AI-native, Microsoft Project Online alternative

See related servers & alternatives →

Related MCP servers

Browse all →

Related guides

Hand-picked reading to help you choose and use Other servers.