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Merovingian MCP Server

by evo-hydra

merovingian_add_consumer

Register a consumer relationship between two repositories to track cross-service API dependencies. This enables blast radius analysis by recording which consumer repo calls a specific endpoint on a producer repo.

Instructions

Register a consumer relationship between two repositories.

Call this to tell Merovingian that consumer_repo calls an endpoint on producer_repo. Once registered, merovingian_impact will include this relationship in its blast radius analysis.

Args: consumer_repo: Name of the repo that calls the endpoint (e.g. 'web-client') producer_repo: Name of the repo that owns the endpoint (e.g. 'api-server') endpoint_method: HTTP method (e.g. 'GET', 'POST') endpoint_path: Endpoint path (e.g. '/api/v1/transactions')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
consumer_repoYes
endpoint_pathYes
producer_repoYes
endpoint_methodYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool registers a relationship and that this registration feeds into blast radius analysis, confirming it is a mutation. However, it does not mention idempotency, error behavior on duplicates, authentication requirements, or whether the operation is destructive. The description adds some context but misses important behavioral traits for a tool with no annotation safety net.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise: a one-sentence purpose, a one-sentence usage context, and a clean Args list. No unnecessary words or repetition. The critical information is front-loaded. Every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The description covers the tool's purpose, when to call it, and all parameter meanings. An output schema exists (mentioned in context signals), so the lack of return details is acceptable per guidelines. However, it omits information on error scenarios (e.g., duplicate relationships) and any prerequisites. For a registration tool with no annotations and four required params, it is largely complete but could be slightly more thorough.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters5/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the description must compensate. It provides a detailed Args section with explanations and example values for each of the four parameters ('consumer_repo', 'producer_repo', 'endpoint_method', 'endpoint_path'). Each parameter is clearly defined (e.g., 'Name of the repo that calls the endpoint (e.g. 'web-client')'). This fully compensates for the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Register a consumer relationship between two repositories.' It uses specific verbs and resources, and the subsequent sentence ('Call this to tell Merovingian that consumer_repo calls an endpoint on producer_repo') provides concrete detail. The sibling tools include 'merovingian_consumers' (likely list) and 'merovingian_impact' (analysis), so this tool's distinct role is well-defined.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides explicit context for when to call this tool: before impact analysis, to register a dependency. It also explains the consequence ('merovingian_impact will include this relationship'). However, it does not mention when not to use it or suggest alternative tools among the siblings (e.g., maybe 'merovingian_register' for other registrations). The guidance is clear but lacks exclusion criteria.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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