Build MCP servers with TypeScript on Cloudflare Workers, preventing 20 documented production issues.
Works with
Supports tools, resources, prompts, tasks, and three authentication patterns (API keys, OAuth, Zero Trust) with built-in Cloudflare service integrations (D1, KV, R2, Vectorize)
Requires fresh McpServer instance per HTTP request and StreamableHTTPServerTransport for production; SSE transport is deprecated
Prevents critical issues including server instance reuse breaking concurrent sess
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versiontypescript-mcpExecute the skills CLI command in your project's root directory to begin installation:
Fetches typescript-mcp from jezweb/claude-skills and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate typescript-mcp. Access via /typescript-mcp in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Automate repetitive workflows and reduce manual effort
Example
Generate reports, summarize documents, draft communications
Save 3-5 hours per week on routine tasks
Learn new skills, understand complex topics, get expert guidance
Example
Explain concepts, provide examples, suggest learning resources
Accelerate learning and skill development by 2x
Enhance output quality through reviews, suggestions, and refinements
Example
Review drafts, suggest improvements, catch errors
Improve work quality by 30-40% with less effort
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Last Updated: 2026-01-21 Versions: @modelcontextprotocol/[email protected], [email protected], [email protected] Spec Version: 2025-11-25
npm install @modelcontextprotocol/sdk@latest hono zod
npm install -D @cloudflare/workers-types wrangler typescript
Transport Recommendation: Use StreamableHTTPServerTransport for production. SSE transport is deprecated and maintained for backwards compatibility only. Streamable HTTP provides better error recovery, bidirectional communication, and simplified deployment.
Basic MCP Server:
import { McpServer } from '@modelcontextprotocol/sdk/server/mcp.js';
import { StreamableHTTPServerTransport } from '@modelcontextprotocol/sdk/server/streamableHttp.js';
import { Hono } from 'hono';
import { z } from 'zod';
const server = new McpServer({ name: 'my-mcp-server', version: '1.0.0' });
server.registerTool(
'echo',
{
description: 'Echoes back input',
inputSchema: z.object({ text: z.string() })
},
async ({ text }) => ({ content: [{ type: 'text', text }] })
);
const app = new Hono();
app.post('/mcp', async (c) => {
const transport = new StreamableHTTPServerTransport({
sessionIdGenerator: undefined,
enableJsonResponse: true
});
// CRITICAL: Set error handler to catch transport errors
transport.onerror = (error) => {
console.error('MCP transport error:', error);
};
// CRITICAL: Close transport to prevent memory leaks
c.res.raw.on('close', () => transport.close());
await server.connect(transport);
await transport.handleRequest(c.req.raw, c.res.raw, await c.req.json());
return c.body(null);
});
export default app; // CRITICAL: Direct export, not { fetch: app.fetch }
Deploy: wrangler deploy
API Key (KV-based):
app.use('/mcp', async (c, next) => {
const apiKey = c.req.header('Authorization')?.replace('Bearer ', '');
const isValid = await c.env.MCP_API_KEYS.get(`key:${apiKey}`);
if (!isValid) return c.json({ error: 'Unauthorized' }, 403);
await next();
});
Cloudflare Zero Trust:
const jwt = c.req.header('Cf-Access-Jwt-Assertion');
const payload = await verifyJWT(jwt, c.env.CF_ACCESS_TEAM_DOMAIN);
Tasks enable long-running operations that return a handle for polling results later. Useful for expensive computations, batch processing, or operations that may need input.
Task States: working → input_required → completed / failed / cancelled
Server Capability Declaration:
const server = new McpServer({
name: 'my-server',
version: '1.0.0',
capabilities: {
tasks: {
list: {},
cancel: {},
requests: {
tools: { call: {} }
}
}
}
});
Tool with Task Support:
server.registerTool(
'long-running-analysis',
{
description: 'Analyze large dataset',
inputSchema: z.object({ datasetId: z.string() }),
execution: { taskSupport: 'optional' } // 'forbidden' | 'optional' | 'required'
},
async ({ datasetId }, extra) => {
// If invoked as task, extra.task contains taskId
const result = await performAnalysis(datasetId);
return { content: [{ type: 'text', text: JSON.stringify(result) }] };
}
);
Client Task Request:
{
"method": "tools/call",
"params": {
"name": "long-running-analysis",
"arguments": { "datasetId": "abc123" },
"task": { "ttl": 60000 }
}
}
Task Lifecycle:
task param → receives taskIdtasks/get with taskIdcompleted, client calls tasks/result to get outputtasks/cancel to abort📚 Spec: https://modelcontextprotocol.io/specification/2025-11-25/basic/utilities/tasks
Servers can now include tool definitions in sampling requests, enabling server-side agent loops.
Use Case: Server needs to orchestrate multi-step reasoning using LLM + tools without custom frameworks.
// Server initiates sampling with tools available
const result = await server.requestSampling({Prerequisites
Time Estimate
15-45 minutes depending on use case complexity
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.
✗ Avoid when
Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.
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typescript-mcp is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
Useful defaults in typescript-mcp — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for typescript-mcp matched our evaluation — installs cleanly and behaves as described in the markdown.
Solid pick for teams standardizing on skills: typescript-mcp is focused, and the summary matches what you get after install.
typescript-mcp fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
We added typescript-mcp from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
Keeps context tight: typescript-mcp is the kind of skill you can hand to a new teammate without a long onboarding doc.
typescript-mcp reduced setup friction for our internal harness; good balance of opinion and flexibility.
typescript-mcp has been reliable in day-to-day use. Documentation quality is above average for community skills.
We added typescript-mcp from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
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