MCP server/cloud

Conduit MCP Server

Connect any AI agent to your data streams.

useconduit/mcp ↗by useconduitupdated
1

Add it to Claude Code

claude mcp add -e "CONDUIT_API_KEY=${CONDUIT_API_KEY}" conduit-0c97 -- npx -y @useconduit/mcp
Required:CONDUIT_API_KEY+ 1 optional
2

Make your agent remember this setup

conduit-0c97's config, env vars, and the gotchas you hit — recalled in every future Claude Code, Cursor, and Codex session. 

npx conare@latest

Free · one command · indexes the sessions already on disk. Set up in the browser instead →

What it does

  • One endpoint for multiple protocols including HTTP, WebSocket, and MQTT
  • AI-powered automated schema detection
  • Real-time event forwarding to webhooks and brokers
  • Historical event backfilling and replay capabilities
  • MCP-native integration for AI agents

Tools 12

conduit_list_streamsList all data streams
conduit_get_schemaGet schema for a stream (columns, types, codecs)
conduit_create_streamCreate a new stream
conduit_ingestSend events to a stream
conduit_list_eventsQuery events with pagination & time range filters
conduit_add_forwardAdd a forwarding destination (HTTP, MQTT, or WebSocket) with auth options
conduit_stream_statsGet ingestion statistics (event count, rate, latency)
conduit_analyze_schemaAnalyze a JSON payload for optimal schema
conduit_feedbackSubmit feedback to the Conduit team
conduit_backfillReplay historical events to forwarding destinations
conduit_backfill_statusCheck backfill job progress or list all jobs
conduit_time_rangeGet earliest/latest event timestamps for a stream

Environment Variables

CONDUIT_API_KEYrequiredYour Conduit API key
CONDUIT_API_URLCustom API endpoint

Try it

→List all available data streams in my Conduit account.
→Analyze the schema for the 'sensors' stream and show me the latest 10 events.
→Set up a new HTTP forward for the 'logs' stream to my data warehouse endpoint.
→Check the ingestion statistics for the 'user-activity' stream.
→Replay historical events from the last 24 hours for the 'transactions' stream.
Original README from useconduit/mcp

@useconduit/mcp

MCP server for Conduit — connect any AI agent to your data streams.

📖 API Docs · 🌐 Website · 📦 npm · 💻 GitHub

Quick Start

Get an API key from platform.usecondu.it/tokens, then add to your AI editor config:

Claude Code / Claude Desktop

Add to ~/.claude/settings.json:

{
  "mcpServers": {
    "conduit": {
      "command": "npx",
      "args": ["-y", "@useconduit/mcp"],
      "env": {
        "CONDUIT_API_KEY": "conduit_sk_..."
      }
    }
  }
}

Cursor

Add to .cursor/mcp.json in your project:

{
  "mcpServers": {
    "conduit": {
      "command": "npx",
      "args": ["-y", "@useconduit/mcp"],
      "env": {
        "CONDUIT_API_KEY": "conduit_sk_..."
      }
    }
  }
}

Windsurf

Add to ~/.codeium/windsurf/mcp_config.json:

{
  "mcpServers": {
    "conduit": {
      "command": "npx",
      "args": ["-y", "@useconduit/mcp"],
      "env": {
        "CONDUIT_API_KEY": "conduit_sk_..."
      }
    }
  }
}

Environment Variables

Variable Required Default Description
CONDUIT_API_KEY ✅ — Your Conduit API key
CONDUIT_API_URL — https://api.usecondu.it Custom API endpoint

Tools

Tool Description
conduit_list_streams List all data streams
conduit_get_schema Get schema for a stream (columns, types, codecs)
conduit_create_stream Create a new stream
conduit_ingest Send events to a stream
conduit_list_events Query events with pagination & time range filters
conduit_add_forward Add a forwarding destination (HTTP, MQTT, or WebSocket) with auth options
conduit_stream_stats Get ingestion statistics (event count, rate, latency)
conduit_analyze_schema Analyze a JSON payload for optimal schema
conduit_feedback Submit feedback to the Conduit team
conduit_backfill Replay historical events to forwarding destinations
conduit_backfill_status Check backfill job progress or list all jobs
conduit_time_range Get earliest/latest event timestamps for a stream

Resources

URI Description
conduit://streams All streams
conduit://streams/{name} Stream details + schema
conduit://stats Platform-wide statistics

API Documentation

Full interactive API docs are available at api.usecondu.it/docs (powered by Scalar).

Key endpoints:

Method Endpoint Description
POST /v1/{tenant}/{stream} Ingest events (any protocol: HTTP, WebSocket, MQTT)
GET /api/v1/streams List streams
GET /api/v1/streams/{name} Stream details + schema
GET /api/v1/streams/{name}/events?from=&to=&limit= Query events with time range
GET /api/v1/streams/{name}/stats Ingestion statistics
GET /api/v1/streams/{name}/schema-history Schema evolution history
POST /api/v1/streams/{name}/forwards Add forwarding destination
POST /api/v1/streams/{name}/backfill Start backfill job
GET /api/v1/streams/{name}/backfill List backfill jobs
GET /api/v1/streams/{name}/time-range Event time range
POST /api/v1/tokens Create API token
GET /api/v1/account Account info + usage

Machine-readable API specs:

What is Conduit?

Conduit is the lightweight data layer between your services. Send any JSON — schemas aren't defined, they emerge. And they evolve as your sources do.

  • One endpoint, any protocol — HTTP, WebSocket, MQTT/S on the same path
  • AI-powered schema detection — zero configuration, runs locally (your data never leaves)
  • Real-time forwarding — HTTP webhooks, MQTT brokers, WebSocket endpoints with full auth options
  • Backfill — replay historical events to new destinations
  • Built for agents — MCP-native from day one, feedback loop included
  • European infrastructure 🇪🇺 — all data hosted and processed in the EU, GDPR-compliant by design

How agents use Conduit

Agent: "I see live sensor data flowing in. I'll pipe it to our datawarehouse and add hot storage."

▸ conduit_list_events(stream: "sensors", limit: 1000)
  ↳ 1,000 events · 18.4 MB raw → 1.1 MB stored (94% compressed)

▸ conduit_add_forward(stream: "sensors", type: "http", url: "https://dwh.acme.io/ingest")
  ↳ Destination added · forwarding to datawarehouse

▸ conduit_add_forward(stream: "sensors", type: "mqtt", broker: "mqtt://redi

Frequently Asked Questions

What are the key features of Conduit MCP?

One endpoint for multiple protocols including HTTP, WebSocket, and MQTT. AI-powered automated schema detection. Real-time event forwarding to webhooks and brokers. Historical event backfilling and replay capabilities. MCP-native integration for AI agents.

What can I use Conduit MCP for?

Piping live sensor data to a data warehouse for long-term storage. Forwarding real-time application logs to an external monitoring service. Replaying historical transaction events to test a new data processing pipeline. Automating schema management for unstructured JSON data streams.

How do I install Conduit MCP?

Install Conduit MCP by running: npx -y @useconduit/mcp

What MCP clients work with Conduit MCP?

Conduit MCP works with any MCP-compatible client including Claude Desktop, Claude Code, Cursor, and other editors with MCP support.

Conare · memory for coding agents

Turn this server into reusable context

Keep Conduit MCP docs, env vars, and workflow notes in Conare so your agent carries them across sessions.

Set up free$npx conare@latest

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