The July 2026 release of Informatica MCP servers and AI Agent Engineering includes the following new features and enhancements.
Shared MCP servers
In August 2026, we've rolled out the following shared MCP server as part of the July 2026 release:
Audit Management
Enables AI agents to browse IDMC audit and security logs.
CDGC Data Quality Score
Enables AI agents to retrieve data quality scores for business and technical assets using Data Governance and Catalog.
Connection Management
Enables AI agents to create, manage, test, monitor, and validate connections to external systems with full CRUD operations over the connection metadata.
IDMC Asset Promotion
Enables AI agents to promote IDMC assets in the software development lifecycle, from development to production, automating multi-step promotion workflows and failure diagnostics.
IDMC Troubleshooting
Enables AI agents to investigate and resolve operational issues by providing real-time visibility into IDMC schedules, assets, mappings, connections, jobs, Secure Agents, and Data Ingestion and Replication tasks.
Note:
This MCP server is available for preview.
IPU Management
Enables AI agents to export IPU usage data grouped by organization, project, asset, or job in IDMC, and to track corresponding export jobs.
Log Management
Enables AI agents to retrieve historical Data Integration activity logs, session logs, and error logs from the Informatica IDMCMonitor service.
Secure Agent Management
Enables AI agents to observe and repair the Secure Agent groups that power IDMC workloads.
User Management
Enables AI agents to automate IDMC user onboarding, role provisioning, and offboarding to accelerate user access, eliminate manual IT overhead, and enforce least privilege security policies.
In August 2026, we've enhanced the following shared MCP server as part of the July 2026 release:
Customer Identification
The get_related_records tool is added. This tool retrieves relationships and related records of a master record, identified by its business ID.
Job Management
We added the following tools that enable AI agents to orchestrate, monitor, and manage the lifecyle of Data Integration tasks and taskflows:
- Get_dynamic_mapping_task_status
- Get_taskflow_status
- List_running_jobs
- Resume_taskflow_fault_entry
- Resume_taskflow_fault_skip
- Run_dynamic_mapping_task
- Run_linear_taskflow
- Run_masking_task
- Run_powercenter_task
- Run_published_taskflow
- Run_replication_task
- Run_synchronization_task
- Search_completed_jobs
- Search_task asset
- Stop_dynamic_mapping_task
- Terminate_taskflow_runs
The following shared MCP servers are added in July 2026:
Catalog Discovery
Allows your AI agents to discover and explore enterprise data assets in Cloud Data Governance and Catalog (CDGC).
Catalog Enrichment
Allows your AI agents to enrich and curate enterprise data assets in Cloud Data Governance and Catalog.
You can create composite MCP servers in AI Agent Engineering. Create composite MCP servers to expose your Application Integration processes as MCP tools that your AI agents can securely access and use. Exposing processes through MCP helps to establish a trusted context for your AI agents and helps ground the model to your trusted business data.