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Agentic Fabriq

Give agents scoped tool access with centralized credentials, policy checks and activity records

Pricing
Developer Free plan with 20,000 calls/month; Launch $50/month with 200,000 calls; Growth $300/month with 2,000,000 calls; Enterprise and self-hosted options custom
Free plan
Yes; developer plan with 20,000 monthly calls
Platforms
Managed cloud, Web dashboard, API, MCP; custom Kubernetes deployment

Tool Information

Agentic Fabriq
Agentic Fabriq
Updated: September 2026
Tool type: AI Agent Identity And Access Platform
Pricing: Developer Free plan with 20,000 calls/month; Launch $50/month with 200,000 calls; Growth $300/month with 2,000,000 calls; Enterprise and self-hosted options custom
Free plan: Yes; developer plan with 20,000 monthly calls
Platforms: Managed cloud, Web dashboard, API, MCP; custom Kubernetes deployment
Login required: Yes for workspace and connected accounts
API: Yes; REST APIs,Python SDK,CLI and MCP endpoint
Browser extension: No official browser extension verified
Mobile app: No official native mobile app verified
AI models: Model-independent control layer; not a standalone generation model
Developer: Agentic Fabriq

About Agentic Fabriq

Agentic Fabriq provides identity, permission and credential infrastructure for AI agents that use external tools. Instead of giving every agent its own collection of raw credentials and custom access logic, a developer routes requests through a common control layer. Fabriq evaluates the agent, the user it represents and the requested resource before allowing the action. The product serves both agents inside a company and agents embedded in a customer-facing application.

Identity and delegated access

Each agent can have a distinct identity, with access constrained by the permissions of the relevant user. Credentials and tokens are managed centrally rather than stored directly by the agent. For a product serving external customers, each customer connects their own accounts. For internal deployments, the enterprise offering adds organization-wide governance around employee access and shared agents.

Tools and visibility

The platform provides SDK and API interfaces, a Python SDK, a command-line tool and an MCP endpoint. The website names agent frameworks such as LangChain, CrewAI, AutoGen and OpenAI Agents, alongside business services including Gmail, Slack, GitHub and Drive. Activity records and live sessions help teams inspect what a registered agent requested and how policy handled it.

Plans and deployment

Developer plans are based on calls made through Fabriq. The free allowance supports evaluation, while Launch and Growth increase included usage and provide additional capabilities. Enterprise plans address broader governance needs such as approvals, SSO and organization-level audit trails. A custom arrangement can deploy the service into the customer’s Kubernetes environment on supported cloud infrastructure.

Practical role

Fabriq is an access-control component rather than a content-generation model. Teams still define the tools, scopes and policies appropriate to their agent. A useful evaluation registers one agent, connects a limited tool set and checks allowed and blocked requests before expanding deployment.

Key features
  • Distinct identities for agents and delegated users.
  • Fine-grained policies for tools and resources.
  • Central credential vault and token exchange.
  • REST APIs, Python SDK, CLI and MCP access.
  • Request logs and live activity visibility.
  • Developer and enterprise deployment paths.
  • Custom Kubernetes deployment option.
Use cases
Adding tool permissions to an agent,Managing customer-connected accounts,Auditing agent actions,Centralizing agent credentials,Governing enterprise AI deployments
How to use
  1. Choose the developer or enterprise route for the deployment.
  2. Create a workspace and register the agent.
  3. Define the users the agent may act for.
  4. Connect required tools and credential sources.
  5. Set resource and action scopes for the agent.
  6. Connect through the SDK, API or MCP interface.
  7. Test both permitted and blocked requests.
  8. Inspect request records and refine policies.
  9. Deploy the configuration and monitor usage and access changes.
Best for
Agent Developers, Enterprise Security Teams, AI Platform Teams
Integrations
Prebuilt integrations plus OpenAPI services,MCP servers and guarded Postgres; examples include Gmail,Google Drive,Calendar,Slack,GitHub,Notion,Microsoft 365,Salesforce and many others
Commercial use
Designed for commercial agent products and enterprise deployments under plan terms

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