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peakacom

peaka-mcp-server

Official
by peakacom

peaka_list_connections

Read-only

List all data source connections in a Peaka project to discover wired-up sources. Returns each connection's ID, name, type, and callback URL for OAuth-based connections.

Instructions

List all data source connections in the Peaka project. Returns each connection's id, name, type, and (for OAuth-based connections) callback URL. Useful for discovering what data sources are wired up; pair with peaka_get_connection_detail for connection-specific configuration.

If you do not already know the projectId for the current task, call peaka_list_projects first and ask the user which project to use. Remember the chosen projectId for subsequent calls in this conversation.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectIdYesThe Peaka project ID to run against.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.11.0

TDQS

A4.5/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the non-mutating nature is covered. The description adds helpful return-value expectations (id, name, type, callback URL) and a user-confirmation workflow, but it does not disclose additional behavioral caveats such as pagination, permissions, or failure modes.

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 succinct and front-loaded: purpose, return contract, sibling routing, and prerequisite workflow each earn their place. There is no filler or repetition that dilutes the guidance.

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

Completeness5/5

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

For a one-parameter read-only tool with no output schema, the description is complete: it explains what is returned, how to handle the required projectId, and where to go for more detail. An agent has enough context to call the tool correctly without needing additional structured fields.

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

Parameters4/5

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

The schema covers the single parameter 100% with a clear description, so the baseline is 3. The description adds practical meaning by explaining how to obtain an unknown projectId via peaka_list_projects and instructing the agent to remember it for subsequent calls, which goes beyond the bare schema definition.

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 uses a specific verb ('List') and clearly identifies the resource: 'all data source connections in the Peaka project.' It also distinguishes itself from the related sibling by explicitly mentioning peaka_get_connection_detail for connection-specific configuration, making the tool's scope immediately clear.

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

Usage Guidelines5/5

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

The description offers explicit usage guidance: it says to pair with peaka_get_connection_detail when configuration details are needed, and it directs the agent to call peaka_list_projects first if projectId is unknown. This is concrete, actionable routing that leaves little ambiguity.

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