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freedom-mcp

by com.getfreedomos

start_github_app_claim

Start connecting GetFreedomOS (the FreedomOS GitHub App) for this company. Returns an install_url the operator must open in a browser, pick the org and repos (e.g. linnetlegacies/freedom-ai), then return to FreedomOS Pulse which finishes the bind. Does not install from GitHub's side and does not use GitHub Copilot MCP. If already connected, still returns status plus a fresh install URL for adding another org. Use when the operator or CoS needs to bind GetFreedomOS onto a GitHub org/repo from FreedomOS.

Routing: Connect / bind GetFreedomOS GitHub App → this tool (returns install_url). Not request_connector GitHub.

[write-tier — first use may require a manager's approval; a from-now-on approval makes future calls seamless, a just-once approval re-asks next time.]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
companyIdYesFreedomOS company id to act within (you must be a member). Required for company-scoped tools.

TDQS

A4.6/5.0
Behavior5/5

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

With no annotations, the description carries the full burden. It disculse the manual out-of-band step, notes that it 'Does not install from GitHub's side,' clarifies lack of GitHub Copilot MCP usage, handles the already-connected case, and flags the write-tier approval requirement. This gives agents an unusually complete picture of actual invocation behavior.

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?

The description is a bit long, but every sentence serves a purpose: it explains the return, the manual flow, what the tool cannot do, the alternative tool, and the approval caveat. The routing and write-tier hints are extra but genuinely useful, so the length is justified.

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?

For a one-parameter auth-flow tool with no annotations or output schema, the description is remarkably complete: it gives the exact returned value, the operator-side steps, the finish-on-Pulse step, the already-connected behavior, and the approval warning. Nothing material needed to call the tool successfully is missing.

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 already fully covers the single parameter companyId. The description implies it by saying 'for this company,' but doesn't add materially new detail like format, validation, or membership beyond what the schema already states. Baseline 3 is appropriate for 100% schema coverage.

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 names a specific action ('Start connecting GetFreedomOS...'), the resource (the FreedomOS GitHub App), and the concrete outcome (returns install_url). It also disambiguates from sibling tools by explicitly saying 'Not request_connector GitHub.' Strong differentiation.

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?

Explicitly states when to use it: 'Use when the operator or CoS needs to bind GetFreedomOS onto a GitHub org/repo from FreedomOS.' It also tells the agent what not to use (request_connector GitHub) and notes the manual browser/install step. This is ideal routing 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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TDQS

A3.6/5.0
Disambiguation4/5

The tool set is heavily disambiguated by detailed routing descriptions, domain prefixes, and lifecycle verbs, so most tools have a clear intended purpose. However, at 297 tools there are still close pairs and overlapping decision surfaces (e.g., approval workflows, 'what should I work on' readers, multiple finance/ads readers) that require careful description reading to avoid misselection.

Naming Consistency4/5

Naming is predominantly consistent snake_case verb_noun with strong domain prefixes like shopify_, x_, posthog_, and list_/create_/update_ patterns. Minor inconsistencies exist, such as several collection-returning tools using get_ (get_team_members, get_icps, get_okrs) instead of list_, and some generate_ vs create_ vs draft_ verbs, but the pattern is still predictable overall.

Tool Count1/5

297 tools is an extreme outlier and far beyond a usable MCP tool surface. Even a large suite has no justification for this count in one server; the agent would struggle to select among hundreds of similarly descriptive tools, and the natural 3-15 tool range is exceeded by nearly 20x.

Completeness4/5

The individual domains represented — OKRs, CRM/leads, Shopify, content pipelines, ads, PostHog, team hiring, knowledge, finance, and session management — are covered remarkably well with full lifecycle patterns. Minor gaps exist, such as no full deal CRUD, no delete for several Google/Shopify artifacts, and some analytical surfaces being read-heavy, but most workflows can be completed without dead ends.

Resources