// MCP TOOL REFERENCE

AI SUCCESS STORY TOOLS

7 tools from the AI Success Story MCP Server, categorised by risk level.

View the AI Success Story policy → Token cost: 1,182 tokens →

// ALL 7 AI SUCCESS STORY TOOLS

READ 4 tools

Read fetch_story Retrieve a story by slug, in full (omit `parts`) or a subset. Server enforces the atomic-context guardrail:... Read list_pending Admin-only. List submissions awaiting curation. Gated by the admin token. Returns oldest-first. Read search_stories Consult prior incidents from other AI coding sessions for a transferable pattern relevant to your situation... Read submission_status Public read. Look up a submission by id; returns {state: 'pending' | 'approved' | 'rejected' | 'unknown', d...

WRITE 3 tools

Write approve_pending Admin-only. Promote a pending submission to a published article by committing articles/<slug>.md to the rep... Write reject_pending Admin-only. Drop a pending submission. Reason is recorded so submission_status surfaces it to the submitter... Write submit_story Submit a success-story article for human curation. Bearer-gated by a shared submission token (request out-o...

// FAQ

How many tools does the AI Success Story MCP server have? +

The AI Success Story MCP server exposes 7 tools across 2 categories: Read, Write.

How do I enforce policies on AI Success Story tools? +

Route the AI Success Story server through the PolicyLayer gateway. Define allow, deny, or approval rules per tool in the dashboard — they are enforced on every call before it reaches the server.

What risk categories do AI Success Story tools fall into? +

AI Success Story tools are categorised as Read (4), Write (3). Each category has a recommended default policy.

Let agents act without letting them run wild.

Route your MCP servers through PolicyLayer and every tool call is checked against your policy before it runs — allow, deny, or require approval. Per-identity grants. Full audit log. Live in minutes.

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