Skip to main content
Glama
Sign In

PeoplePerHour MCP Server and API by Cotlet

by dev.cotlet
OverviewDiscussionsAdmin

List my projects in PeoplePerHour

peopleperhour_list_my_projects
Read-onlyIdempotent

List my projects in the user's own PeoplePerHour account from ChatGPT, Claude or any AI agent. Returns how to do it in PeoplePerHour step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's PeoplePerHour Cloud Browser. PeoplePerHour's official API: PeoplePerHour has no public API and no developer docs (checked 12 Oct 2026).

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": "peopleperhour_list_my_projects"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.9/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower, but the description adds genuinely non-obvious behavior: the tool 'opens nothing by itself' and must be followed by browser tool calls. The note that PeoplePerHour has no public API is useful context for why a browser-driven path is required, though it is undated in a way that undercuts its rigor.

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

Conciseness3/5

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

The core message is front-loaded and no sentence is wasted, but the phrasing is tangled — 'Returns how to do it in PeoplePerHour step by step ... then do it with the cotlet_browser_* tools' is a run-on that forces re-reading. The 'from ChatGPT, Claude or any AI agent' branding clause and the repeated title add little.

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?

With no parameters and no output schema, the description carries the burden and mostly does: it explains what comes back (step-by-step instructions) and what to do next. It never states authentication/session prerequisites for the PeoplePerHour Cloud Browser, which is the one real gap for a tool that depends on a logged-in user session.

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 tool takes zero parameters, so the baseline is 4. The description correctly implies no inputs are needed and instead spends its words on return content and follow-up actions, which is the right allocation for a parameterless tool.

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

Purpose4/5

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

The description names a specific resource (my projects in the user's PeoplePerHour account) and explicitly states what the tool actually returns: step-by-step screens/buttons/fields rather than data. This corrects the misleading 'list' verb in the name, but the reader must reconcile the name with the real behavior, so it stops short of a clean 5.

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?

It gives a concrete workflow: call this to get the click-path, then execute it with the cotlet_browser_* tools inside the user's PeoplePerHour Cloud Browser. It does not name any sibling peopleperhour_* tool as an alternative or state when this is the wrong choice, so it is clear context without explicit exclusions.

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

All PeoplePerHour MCP Server and API by Cotlet toolsInspect
Try in Browser
One endpoint for every MCP toolRayrun runs every MCP server behind one URL and holds the credentials. Each call is decided per client, tool, and argument, then recorded.ray.runAd

Glama MCP Gateway

Add one secure layer between your agents and this server.

Resources