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whats-running-mcp

whats-running-mcp

by stcmain
OverviewSchemaSourceRelated ServersDiscussionsAdmin
JavaScript
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agent_sessions

Lists currently running AI-agent processes, distinguishing terminal-attached sessions from detached/orphan ones by reading OS data directly.

Instructions

List AI-agent processes actually running right now (Claude Code, Codex, Aider, ...). Separates terminal-attached sessions (a human can see them) from detached/orphan ones. Reads ps/lsof directly — never transcripts or docs. Patterns configurable via WR_AGENT_PATTERNS.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "agent_sessions"
  }
}

Input Schema

NameRequiredDescriptionDefault
include_detachedNoAlso list background/orphan agent processes with no terminal (default true)

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden of explaining behavior. It discloses that it reads ps/lsof directly, never touches transcripts or docs, and that patterns are configurable via WR_AGENT_PATTERNS. This gives essential insight into how the tool operates, though it omits details like required permissions or edge-case behavior.

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 three sentences long, all of which are informative and contribute to understanding the tool. It front-loads the primary purpose ('List AI-agent processes actually running') and avoids any filler or redundancies.

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?

For a simple read-only list tool with one optional boolean parameter and no output schema, the description covers the essential aspects: purpose, data source, session distinction, and configuration. It doesn't detail the return structure, but that omission is acceptable given the straightforward nature of the tool and the lack of output schema.

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 input schema has 100% coverage for the only parameter, include_detached, with a clear description of its meaning. The tool description implies the detached/orphan distinction but does not directly explain the parameter's effect. Since the schema is thorough, the baseline of 3 applies, and the description adds no additional parameter-specific meaning.

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: 'List AI-agent processes actually running right now' with concrete examples (Claude Code, Codex, Aider). It distinguishes itself from siblings by focusing specifically on AI agents and reading from ps/lsof, rather than generic system stats or daemons.

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 clear context for when to use the tool: to see currently running AI-agent processes, distinguishing terminal-attached from detached ones. It doesn't explicitly name alternatives, but the scope is specific enough to imply when it would be appropriate, and there are no exclusions.

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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