Retrieve a story by slug, in full (omit parts) or a subset. Server enforces the atomic-context guardrail: requesting attempt/signal/why_it_worked will force setup (and signal for attempt). forced_parts and forced_parts_reason make this observable.
Part of the AI Success Story server.
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AI agents call fetch_story to retrieve information from AI Success Story without modifying any data. This is common in research, monitoring, and reporting workflows where the agent needs context before taking action. Because read operations don't change state, they are generally safe to allow without restrictions -- but you may still want rate limits to control API costs.
Even though fetch_story only reads data, uncontrolled read access can leak sensitive information or rack up API costs. An agent caught in a retry loop could make thousands of calls per minute. A rate limit gives you a safety net without blocking legitimate use.
Read-only tools are safe to allow by default. No rate limit needed unless you want to control costs.
{
"version": "1",
"default": "deny",
"tools": {
"fetch_story": {}
}
}See the full AI Success Story policy for all 7 tools.
These attack patterns abuse exactly the kind of access fetch_story gives an agent. Each links to the full case and the policy that stops it:
Other read tools across the catalogue. The same approach applies to each: allow, with a rate cap to control cost.
Retrieve a story by slug, in full (omit parts) or a subset. Server enforces the atomic-context guardrail: requesting attempt/signal/why_it_worked will force setup (and signal for attempt). forced_parts and forced_parts_reason make this observable.. It is categorised as a Read tool in the AI Success Story MCP Server, which means it retrieves data without modifying state.
Register the AI Success Story MCP server in PolicyLayer and add a rule for fetch_story: allow, deny, rate-limit, or require approval. Point your MCP client at the PolicyLayer proxy URL and the rule is enforced on every call, before it reaches AI Success Story. Nothing to install.
fetch_story is a Read tool with low risk. Read-only tools are generally safe to allow by default.
Yes. Add a rate_limit block to the fetch_story rule in your PolicyLayer policy. For example, setting max: 10 and window: 60 limits the tool to 10 calls per minute. Rate limits are tracked per agent session and reset automatically.
Set action: deny in the PolicyLayer policy for fetch_story. The AI agent will receive a policy violation error and cannot call the tool. You can also include a reason field to explain why the tool is blocked.
fetch_story is provided by the AI Success Story MCP server (https://ai-success-story-20f19ed7769b.herokuapp.com/mcp). PolicyLayer sits as a proxy in front of this server to enforce policies before tool calls reach the server.
Deterministic rules across all 7 AI Success Story tools. Per-identity grants. Full audit log. Live in minutes. Nothing to install.
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