Connects AI assistants to SCF Controls Platform data and workflows for compliance, evidence, risk, and vendor management.
Copy the AI prompt to install this server into Claude Code, Cursor, or another agent — or use 1-click editor setup below.
💡 Paste the JSON block into your client's configuration file under mcpServers, then restart the application.
Inspect callable tools, capabilities, and parameters exposed to AI agents by MCP Server Scf.
scf_list_controlsList SCF security controls from the reference catalog. Returns paginated controls with SCF ID, title, description, and mapped frameworks. Filter by domain, framework, or free-text search.
scf_get_controlGet a single SCF control by ID. Returns description, mapped frameworks, assessment objectives, and linked evidence items from the reference catalog.
scf_list_frameworksList every compliance framework mapped in the SCF catalog (NIST 800-53, ISO 27001, SOC 2, FedRAMP, GDPR, and 350+ more). Returns framework identifiers and display names.
scf_list_domainsList every compliance domain in the SCF taxonomy. Domains group related controls (e.g., GOV = Governance, AST = Asset Management, IAC = Identity & Access Control).
scf_list_evidence_catalogList evidence items from the SCF reference catalog — the 272 standard evidence types that can be collected to demonstrate control implementation. Supports free-text search and pagination.
scf_list_assessment_objectivesList SCF assessment objectives — the 5,736 test criteria used to evaluate control implementation. Optionally filter by control ID; supports free-text search and pagination.
The mcp-server-scf MCP server gives AI assistants an MCP interface to the SCF Controls Platform. It covers the platform’s security compliance and governance data, including 1,451 SCF controls, more than 354 framework mappings, assessment objectives, evidence definitions, implementation status, risks, and vendors.
The server is intended for organizations running the SCF Controls Platform. Agents can use it to browse catalog content, follow control implementation progress, organize evidence, assess risk, manage third-party risk, and work with audit or documentation workflows.
The package runs as a local Node.js process and communicates with an MCP client over standard input and output. The client discovers the available tools and their schemas, then sends tool calls based on the user’s request. The server forwards authenticated operations to the configured SCF Controls Platform instance.
The repository describes 196 tools grouped into 14 domains. These domains cover catalog access, control scoping, evidence, risk, vendors, organization data, capabilities, webhooks, documents, audit engagements, catalog reconciliation, teams, collaboration, and guided journeys.
First deploy or otherwise obtain access to an SCF Controls Platform instance. The README points to the open-source platform, which can be hosted with Docker Compose and includes PostgreSQL, Redis, and MinIO. There is no hosted-platform signup step described in the setup material.
Configure the server with these environment variables:
SCF_API_URL: The base URL of the SCF Controls Platform, such as a local instance at http://localhost:8000.SCF_API_KEY: The API key used to authenticate requests.The key can be supplied through the platform’s environment configuration or created from its Settings → API Keys area after startup. Both variables must be available to the process for live tool calls. The package can also be started through MCP Inspector with npx @modelcontextprotocol/inspector npx -y mcp-server-scf; Inspector can display tool schemas without credentials, but calls return a configuration error when the URL or key is missing.
The mcp-server-scf MCP server organizes its operations as follows:
The server connects to the SCF Controls Platform; it does not provide a standalone compliance database. A reachable platform instance and valid API key are needed for operations that read or change platform data. MCP Inspector can inspect schemas without those credentials, but it cannot complete live requests in that state.
The README distinguishes supported platform operations from deferred or intentionally excluded operations in the repository’s tool-scope documentation. Review that scope before relying on a specific platform workflow.
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