Reach MCP — LinkedIn for AI agents

reach_playbooks

Read-onlyIdempotent

START HERE. Return the catalogue of ready-made LinkedIn playbooks — what this server can actually accomplish, as named workflows rather than raw endpoints. Each entry carries its tool sequence, its prerequisites, and the full instructions to run it. Call this first when the user asks what you can do with their LinkedIn account, or when a request is vague. Pass playbook_id to get one playbook's instructions and then follow them. Use first for a vague request or 'what can you do'; not needed when the user names a precise action.

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": "reach_playbooks"
  }
}

Input Schema

Name	Required	Description	Default
`playbook_id`	No	Id of one playbook from the catalogue, to get its full instructions.
`include_instructions`	No	Also return the full instruction text of every playbook (longer output).

Output Schema

Name	Required	Description	Default
`playbook`	No
`playbooks`	No
`how_to_use`	No

Schema Changelog

Changes observed during successful MCP inspections.

First observedSep 10, 2026

TDQS

A4.6/5.0

Behavior4/5

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

Annotations already declare readOnly, idempotent, non-destructive and non-open-world, so the safety profile is covered. The description adds real behavioral context beyond that: entries contain tool sequences, prerequisites and full instructions, and playbook_id narrows the response to one playbook. It does not discuss pagination or catalogue size, but for a static read-only catalogue that is minor.

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

Conciseness4/5

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

Front-loaded with 'START HERE' and tightly organized, but the when-to-use guidance is stated twice ('Call this first when the user asks what you can do... or when a request is vague' then 'Use first for a vague request or what can you do'). One of those sentences could be dropped without loss.

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?

An output schema exists, so return structure need not be explained, and the description covers everything else an agent needs: that this is a discovery entry point, what each entry contains, how to drill into one, and when to skip it entirely.

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?

Schema description coverage is 100%, so the baseline is 3. The description goes slightly beyond the schema by explaining the intent of playbook_id (retrieve one playbook's instructions 'and then follow them') and flagging that include_instructions produces longer output, which helps an agent decide whether to set it.

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?

States a specific verb and resource ('Return the catalogue of ready-made LinkedIn playbooks') and immediately reframes it as 'what this server can actually accomplish, as named workflows rather than raw endpoints'. That framing distinguishes it from every sibling, which are all single-action endpoint tools.

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?

Gives explicit when-to-use ('Call this first when the user asks what you can do... or when a request is vague') and explicit when-not ('not needed when the user names a precise action'). It also names the follow-up behavior (pass playbook_id, then follow the instructions), leaving nothing to inference.

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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