MCP For Claude Marketplace
Conduit

Conduit MCP Connector for Claude

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Equip your AI agent to observe data streams, manage integration pipelines, and monitor nodes on the Conduit platform.

8 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

Connect your AI agent seamlessly with Conduit, the modern data integration and synchronization platform. Utilizing natural language interactions, users can instruct the AI to oversee active streaming health, check connectors, and extract pipeline logs without accessing the conventional web dashboard interfaces.

What you can do

  • Pipeline Management — Request status overviews of active, paused, or degraded data integration pipelines efficiently.
  • Connector Auditing — Ask the agent to locate specific connectors (source or destination) mapped to your critical infrastructure.
  • Log Evaluation — Fetch recent application logs or streaming output reports via conversation to debug integration errors on the fly.

How it works

  1. Append this integration into your AI application interface securely.
  2. Authorize connections providing the target instance Base URL, corresponding API Key, and an active Admin Password if applicable.
  3. Chat natively instructing your agent to inspect and orchestrate streams through plain text inputs directly.

Who is this for?

  • Data Engineers — Instantly review health metrics regarding continuous synchronization services running between complex databases.
  • DevOps Professionals — Confirm that new pipeline deployments successfully connected endpoints after infrastructure modifications.
  • System Administrators — Request aggregate tracking reports validating if crucial operational data streams function continuously overnight.
data-streamingpipeline-synchronizationreal-time-dataconnector-managementdata-integration

8 tools expose this connector's capabilities to your AI agent.

get_run_status

Returns detailed status, timing, and error information. Retrieve the current status of a specific workflow run

get_workflow

Returns source, destination, and current status. Retrieve detailed information about a specific workflow

list_available_destinations

Retrieve available data destination connector types supported by Conduit

list_available_sources

Retrieve available data source connector types supported by Conduit

list_connections

Retrieve a list of all active source and destination connections

list_workflow_runs

Returns the execution history with status and timestamps for each run. Retrieve the history of runs for a specific workflow

list_workflows

Use this as a starting point to discover workflow IDs for subsequent operations. Retrieve a list of all data integration workflows in Conduit

trigger_workflow

Use list_workflows first to find the workflow ID. Manually trigger a run for a specific workflow

See how to talk to your AI agent using Conduit.

Retrieve the current status of all major pipelines running in the production Conduit instance.

I checked your pipelines successfully. Of the 8 tracked major pipelines running on the queried instance: 7 are currently marked as 'Running' with no latency spikes or recorded disruption alerts. Pipeline ID 'PG_to_Snowflake_04' is however marked 'Degraded' due to a destination connector timeout 4 minutes ago. Do you want further logs related to this degraded element specifically to review the exact recorded error response logged safely here?

Check if there's a configured destination connector named 's3-analytics-bucket' and briefly describe its configuration parameters.

Yes, I located the 's3-analytics-bucket' destination connector attached to your integration pipelines successfully. This configured destination strictly utilizes the official 'builtin:s3' plugin structure. The setup parameters authenticate via attached AWS Keys (redacted), targeting an external region of 'us-east-1', and output streams correctly in a structured JSON payload referencing an established logical path.

Pause the pipeline 'MySQL-to-Kafka' immediately.

I'm sorry, but for safety reasons, I can only inspect pipelines and display logs. I cannot pause, modify, or delete pipelines. Please use the Conduit dashboard to execute this action.

Depending absolutely on how your infrastructure deployed the program (standalone desktop executable, core Docker containerized setups, or external Cloud instance providers), keys are defined at setup. Generally, navigate your hosted interface configurations to visually spot specific 'API section' panels or define standard keys via backend environment base configurations (for Docker setup instances, parameters typically refer natively mapping to 'CONDUIT_API_URL'). Insert keys properly downwards with other core data completely preserving original syntax precisely achieving seamless valid interactive integrations securely effortlessly resolving requirements seamlessly connecting completely natively without technical failures preventing operations running clearly correctly natively actively continuously stably.

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