Inferrex Developers

9. InferrexMCP

InferrexMCP is a Model Context Protocol server. It gives an AI coding tool the same operations as InferrexAPI, as tools. Each tool is one API operation, runs as your workspace, and is held to the same permissions.

The server is at:

https://mcp.inferrex.com/mcp

It speaks Streamable HTTP.

Connect an AI tool

There are two ways to authenticate. Choose one.

  1. In your AI tool, add an MCP server with the address https://mcp.inferrex.com/mcp.
  2. The tool opens the Inferrex sign-in. Sign in.
  3. On "Connect an assistant", check the workspace and the permissions asked for, then approve.

There is no key to copy. Your workspace role still limits every call the assistant makes.

To see or disconnect an assistant: Workspace settings, Connected assistants.

API key (for a machine)

Send an API key in a request header. Either of these works:

X-API-Key: <your API key>
Authorization: Bearer <your API key>

How you set a header depends on your AI tool. Keep the key in the tool's secret store or an environment variable.

A key in the address is refused. https://mcp.inferrex.com/mcp?apiKey=... does not work, because keys in addresses end up in logs and browser history.

A session is tied to the key that opened it. If the key is revoked, the session ends and the next call answers 401.

Clients that only speak the older SSE transport can connect to https://mcp.inferrex.com/sse with a key in a header. Signing in works on /mcp only.

How the tools are named

Tool names are snake_case and start with their area:

Area Tool names start with Examples
Systems connection_, connections_ connection_infer, connections_test_connection
Credentials credential_, credentials_ credential_store, credentials_list_failing_secrets
Mappings mappings_ mappings_get_mapping, mappings_approve_mapping
Flows pipeline_, pipelines_ pipeline_create, pipeline_dry_run
Golden records unified_api_, golden_record_ unified_api_unified_get_action, golden_record_approve_proposal
Repairs heals_ heals_list, heals_answer_heal
Health and safety stops monitoring_ monitoring_get_connection_health
Jobs jobs_ jobs_get_job
Workspace workspace_ workspace_get_environment_overview

Most tools take the record's id as id. Each tool's own description says what it does, what it needs and what it returns. Each tool is also marked as read-only or not, and as destructive or not. A well-behaved AI tool asks you before it runs one that is not read-only.

When a call fails, the tool returns the API's error body (chapter 8) and marks the result as an error.

A first session

Ask your AI tool for an overview. It should call:

  1. workspace_get_active_environment to confirm which environment it is in.
  2. workspace_get_environment_overview with detail: "brief" for what needs attention.

Then work through the sequence. These are the tools for each step.

Connect a system

Step Tool
Ask the API how it signs in connections_detect_auth
Test the address and sign-in. Nothing is stored connections_test_connection
Connect and start the first read connection_infer
Wait for the read connection_status, jobs_get_job
Read what was found connection_manifest
Accept or correct a field connection_approve_field
Leave fields out connections_set_field_inclusion
Approve the system connection_approve

Map and build a flow

Step Tool
Match two systems connections_match
Read the mapping mappings_get_mapping, mappings_list_mappable_fields
Decide links mappings_update_field_mapping, mappings_bulk_update_field
Approve the mapping mappings_approve_mapping
Create a draft flow pipeline_create
Dry run. Nothing is written pipeline_dry_run, then jobs_get_job
Turn it on pipeline_activate
Sync now pipeline_sync
Set when it syncs pipelines_set_pipeline_schedule

Review and watch

Step Tool
List Golden-record changes waiting golden_record_canonical_change_proposals_list
Read one change golden_record_canonical_change_proposals_get
Decide it golden_record_approve_proposal, golden_record_reject_proposal
Trace a value to its source golden_record_get_golden_field_lineage
Health of each system monitoring_get_connection_health
Flows with something waiting pipelines_get_pipeline_attention
A flow's runs pipeline_history
Failed writes pipelines_list_pipeline_quarantine, pipelines_list_quarantine
Repairs and their questions heals_list, heals_get_heal, heals_answer_heal
Safety stops monitoring_stream_circuit_breakers_list, monitoring_list_circuit_breaker_records

Credentials and the conversation

An AI tool sees everything you type and everything a tool returns. You choose how a credential reaches Inferrex.

What needs a person

Some steps cannot be finished by an assistant alone:

Use skills with InferrexMCP

The skills page holds ready-made instructions for AI coding tools: connect a system, map two systems, build a flow, review Golden-record changes, diagnose a failing flow and replace credentials. Each one names the tools to call, in order, with the checks to make before any write.

Next: InferrexCLI, the cloud shell.