Schema | mcp-ai-accountability

mcp-ai-accountability

Describes the environment variables required to run the server.

Name	Required	Description	Default
`RELIABILITY_DB`	No	Path to the reliability database file. For example, './reliability.db'.

Features and capabilities supported by this server

Capability	Details
`tools`	{ "listChanged": false }
`prompts`	{ "listChanged": false }
`resources`	{ "subscribe": false, "listChanged": false }
`experimental`	{}

Functions exposed to the LLM to take actions

Name	Description
start_sessionA	Start a new tracking session for an agent. Call this at the beginning of a multi-step agent run. Returns a session_id that you should pass to later tools.
end_sessionB	End a tracking session and get a quick summary.
record_interactionB	Log one tool-call result. Call this after every important tool use so reliability can be measured.
get_reliability_scoreA	Get the current reliability score (0-100) for an agent. Score = percentage of successful tool calls in the last N hours.
analyze_failuresA	Find the most common failure patterns for an agent. Returns the tools that fail most often and sample error messages.
recommend_improvementsC	Give concrete, actionable recommendations to improve reliability. Based on real failure data.
generate_audit_reportC	Generate a full audit-style report useful for investors, compliance or internal reviews.
check_mcp_healthA	Simple health check against another MCP server (HTTP transport). Useful for multi-agent systems that depend on other MCP servers.

Interactive templates invoked by user choice

Name	Description
No prompts

Contextual data attached and managed by the client

Name	Description
No resources

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