Next-Gen MCP Orchestration

Build intelligent
MCP Infrastructure
without writing code.

Turn developer portals, API documentation, PDFs, and data streams into dynamic, deployment-ready Model Context Protocol servers. Instantly expand the capability index of Claude, Cursor, and custom agent teams.

schemaLive Pipeline
ACTIVE
captive_portalcrawler
picture_as_pdfpdf ingest
Vector Index
Ingesting data...
terminalCursor IDE
smart_toyClaude App
DEPLOYMENT STATUSONLINE
Runtime:Cloudflare Worker
Index Latency:142ms
Ingest SSE Endpoint:/api/mcp/cf-9a...
Core Capabilities

Intelligent Tool Infrastructure for Agent Workforces

Everything you need to compile raw documentation, specifications, and files into structured semantic systems that AI agents can consume securely.

manage_search
Retrieval Engine

Deep Semantic Search & Vector Indexes

Equip AI models with pinpoint context. Instead of basic keyword matches, the system splits content into optimized vectors, matching queries against contextual concepts dynamically.

QUERY:
Click retrieve to run vector match...
cloud_done
Worker Edge

Serverless Edge Hosting

Deploy your MCP server globally onto low-latency Cloudflare Edge networks instantly. Zero server management required.

DEPLOYED LOCATION:Global Edge (275+ PoPs)
RESPONSE TIME:12ms avg
BANDWIDTH:Unlimited SSL
article
Multi-Format

Rich File & Doc Parsing

Accept crawls, structured OpenAPI schema files, raw markdown manuals, PDF documents, or feeds.

.pdf docsweb urlsopenapi.jsonrss feeds
security
Enterprise Security

Fine-Grained Permissions & Safe Sandboxing

Keep your sensitive credentials isolated. The generated server runtime runs inside secure, sandboxed execution scopes. Scopes limit tools to read-only configurations, prevent external injection, and rotate keys regularly.

check_circleSandboxed Execution Engine (V8 Isolated)
check_circleRead-Only File Scopes Configured
lock_openDynamic API Key Injection Rotated
Orchestration Process

From Docs to Live AI Tools

A robust developer experience that bridges static knowledge with real-time agentic execution.

SOURCE INGEST
database_schema01

Ingest & Extract

Provide any doc page, REST reference, or PDF files. The crawler extracts, normalizes, and strips noise from HTML pages or documents automatically.

GET https://docs.mcp.io/api200 OK
➔ Fetching DOM structure...
➔ Found 12 header tags, 4 code blocks
✓ Text successfully extracted (4.2 KB clean Markdown)
COGNITIVE PIPELINE
flowsheet02

Chunk & Vectorize

Documents are split into semantic chunks, embedded using state-of-the-art vector models, and loaded into an isolated vector storage layer for fast retrieval.

VECTOR PIPELINEINDEXING
CHUNKS18 Blocks
DIMENSION1536 (Float32)
SERVER RUNTIME
lan03

Deploy Endpoint

Deploy a global Cloudflare worker instance with standard SSE handlers. AI tools instantly detect functions like semantic search or knowledge retrieval.

mcp.json CONFIGREADY
{
  "mcpServers": {
    "my-server": {
      "url": "https://mcp-worker.dev/sse"
    }
  }
}
Integrations & SDKs

Connect Any AI Client

Whether you use Cursor, Claude Desktop, VS Code, or custom agent systems built with official SDKs.

Seamlessly integrate with Cursor's built-in MCP engine. Add the HTTP+SSE endpoint directly via Cursor Settings.

JSON Config
{
  "mcpServers": {
    "my-server": {
      "url": "https://mcp-worker.dev/sse"
    }
  }
}
Code SDKs

Access the server endpoint programmatically in your favorite codebase context with standard SDK adapters.

import asyncio
from mcp.client.session import ClientSession
from mcp.client.sse import sse_client

async def main():
    async with sse_client("https://mcp-worker.dev/sse") as (read, write):
        async with ClientSession(read, write) as session:
            await session.initialize()
            print(await session.list_tools())

asyncio.run(main())
INSTALLATION:pip install mcp
GitHubstar