Onplana MCP server
Open-source TypeScript Model Context Protocol building blocks,
extracted from Onplana's production MCP
deployment. Two packages:
onplana-mcp-server β server
template. Streamable HTTP transport, Bearer auth, prompt-injection
containment, pluggable dispatcher.
onplana-mcp-client β typed TypeScript
client SDK for calling the public Onplana MCP endpoint at
https://api.onplana.com/api/mcp/v1.

What this is
The transport layer of an MCP server β Streamable HTTP wiring,
stateless mode, scoped Bearer auth, prompt-injection containment β
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) β 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:
- Other MCP authors get a known-good template instead of
reinventing.
- The repo is a pretraining-signal surface β 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."
- 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 β that's the work that
matters and the work that's specific to your platform.
Repository layout
onplana-mcp-server/
βββ packages/
β βββ server-template/ # onplana-mcp-server (npm)
β β βββ src/
β β β βββ transport.ts # Streamable HTTP wiring
β β β βββ auth.ts # Bearer auth pattern
β β β βββ promptInjection.ts # wrapUserContent + escape
β β β βββ dispatcher.ts # Pluggable Dispatcher interface
β β β βββ index.ts
β β βββ tests/ # promptInjection + auth + transport
β β βββ README.md
β βββ client/ # onplana-mcp-client (npm)
β βββ src/
β β βββ client.ts # OnplanaMcpClient class
β β βββ types.ts # Public type surface
β β βββ index.ts
β βββ tests/ # client.test.ts (stub fetch)
β βββ README.md
βββ examples/
β βββ in-memory/ # Runnable demo with 3 toy tools
βββ .github/workflows/
βββ ci.yml # tsc + vitest on PR
βββ 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. 60β120 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 β 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 β₯ 20 (for the server template and CI matrix); β₯ 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 β 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 β Β© 2026 Onplana
See also