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pipeshub-ai

PipesHub MCP Server

Official
by pipeshub-ai
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TypeScript
Hybrid

pipeshub_agents

Read-onlyIdempotent

List all PipesHub agents and their capabilities—available tools and knowledge—so you can pick the right one for your request.

Instructions

List the PipesHub agents configured for this org, each with its capabilities.

Agents are specialized assistants (custom system prompt, tools, knowledge scope). To converse with one, take its agentId and pass it to pipeshub_chat's agentId argument.

Each agent is returned as: { agentId, name, description, systemPrompt, startMessage, tags, webSearch, isActive, toolsets, knowledge }.

  • toolsets — what the agent can DO: each { name, tools } where name is the connector (e.g. jira, gmail) and tools are the runnable tool ids (e.g. jira.create_issue, gmail.send_email).

  • knowledge — what the agent can READ: each { name, type } (e.g. Confluence-2 / Confluence).

Route on toolsets/knowledge, not the name — names and descriptions are often generic or misleading. Match the request to the agent whose tools can actually perform it (e.g. "create a Jira ticket" → the agent whose toolset is jira and whose tools include jira.create_issue). If NO agent has a tool for the requested action, say so — don't force an unrelated agent.

The list may be empty (no agents configured). For plain Q&A when no specific agent is needed, use pipeshub_chat WITHOUT agentId and pick a chatMode: internal_search (org's indexed knowledge) or web_search (live web). Use agentId everywhere an agent is referenced.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
searchNoOptional case-insensitive substring match across agent name, description, and tags. Omit to return every agent.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv2.3.3

TDQS

A4.7/5.0
Behavior5/5

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

Beyond the readOnly/idempotent annotations, the description discloses that the list may be empty, reveals the exact return object shape, explains the semantics of toolsets and knowledge, and warns that names/descriptions can be misleading. This is rich behavioral context that helps the agent interpret results correctly.

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 longer than typical, but every section earns its place: purpose, return structure, field semantics, routing guidance, and empty-list caveat. The use of bullets and bolded field names keeps it scannable and front-loaded with the core purpose.

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?

Despite having no output schema, the description fully compensates by detailing the return object, nested structures, and field meanings. It also covers edge cases (empty list, misleading names) and alternatives, making it complete for an agent to invoke and interpret correctly.

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

Parameters3/5

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

The schema already fully documents the single search parameter with 100% coverage, including case-insensitivity, substring matching, and omit behavior. The description adds no further parameter-level detail, so the baseline of 3 is appropriate.

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 opens with a specific verb and resource: 'List the PipesHub agents configured for this org, each with its capabilities.' It also clearly differentiates this tool from siblings like pipeshub_chat by explaining that this is for listing agents, not conversing with them.

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 gives explicit routing instructions: use this tool to discover agents, take the agentId, and pass it to pipeshub_chat; for plain Q&A use pipeshub_chat without agentId. It also states when to refrain from forcing an unrelated agent, providing clear when-to-use and when-not-to-use guidance.

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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