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Bloomerang MCP Server and API by Cotlet

Log interaction in Bloomerang

bloomerang_log_interaction
Read-onlyIdempotent

Log interaction in the user's own Bloomerang account from ChatGPT, Claude or any AI agent. Returns how to do it in Bloomerang step by step (screens, buttons, fields) and opens nothing by itself; then do it with the cotlet_browser_* tools in the user's Bloomerang Cloud Browser. Bloomerang's official API: Yes, Bloomerang has a REST API for server-to-server integrations, but no MCP server for AI agents (checked 22 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": "bloomerang_log_interaction"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare readOnly/idempotent/non-destructive, and the description reinforces this with the useful clarification that no action is taken and nothing is opened. It also states what is returned (screens, buttons, fields), which goes beyond what the annotations convey; the API/MCP availability aside adds little behavioral value.

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 essential flow (returns steps, use browser tools) is present, but the lead sentence conflicts with the tool's actual behavior and the trailing note about Bloomerang's REST API and dated MCP-check is filler that does not help an agent call the tool.

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 zero-parameter read-only guidance tool with no output schema, the description covers what it returns and how to follow up with browser tools, which is what an agent needs. The main residual gap is the ambiguous name/lead implying it performs the logging itself.

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?

There are zero parameters and the schema is fully described, so the baseline applies. The description correctly implies a parameterless call but contributes no additional parameter meaning because none exists.

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

Purpose3/5

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

The opening sentence says "Log interaction in the user's own Bloomerang account," which reads like a write action, but the next sentence reveals the tool only returns step-by-step instructions and "opens nothing by itself." The real purpose (produce a how-to guide) only becomes clear after reading past the misleading lead, and it is not distinguished from siblings like bloomerang_record_received_gift or bloomerang_create_task.

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 clearly sets up the workflow: call this to get the steps, then execute them with the cotlet_browser_* tools in the user's Bloomerang Cloud Browser. That is actionable routing to the alternative toolset, though there are no explicit exclusions for when this tool is the wrong choice.

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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