meta-social-mcp

graph_api_request

Send raw calls to any Meta Graph API endpoint using the configured access token. Use this escape hatch for operations not covered by other tools.

Instructions

Advanced/escape hatch: make a raw call to any Meta Graph API endpoint with the configured access token. Use this for anything the other tools don't cover yet.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "method": "<method>",
      "path": "<path>"
    },
    "name": "graph_api_request"
  }
}

Input Schema

Name	Required	Description
`path`	Yes	Path starting with '/', e.g. '/me' or '/{page-id}/tabs'.
`method`	Yes
`params`	No	Query params (GET) or form fields (POST).

Schema Changelog

Changes observed during successful MCP inspections.

First observedv1.0.0Sep 8, 2026

TDQS

A4/5.0

Behavior3/5

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

No annotations exist, so the description carries the full behavioral disclosure burden. It does state that calls are 'raw' and use a pre-configured access token, implying direct and potentially destructive operations depending on method. However, it does not mention side effects, rate-limit exposure, or the lack of endpoint-specific response validation, leaving some ambiguity for such a powerful escape-hatch tool.

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?

Two compact sentences deliver the tool's purpose and usage guidance with zero filler. The 'Advanced/escape hatch' label is front-loaded, immediately setting expectations, and the second sentence gives a crisp selection rule.

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 deliberately generic raw-call tool, the combination of description and schema covers what an agent needs to invoke it: the method, path, and params are all specified, and the auth model is disclosed. The absence of an output schema is acceptable because the response is inherently endpoint-dependent; a more verbose description would not meaningfully improve correctness.

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 schema already documents the path format and params semantics ('Query params (GET) or form fields (POST)'), and the method enum is self-explanatory. The description adds no parameter-level detail beyond framing the tool as a raw call to 'any' endpoint, so it neither significantly improves nor degrades the schema's 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 clearly states a specific verb and resource: 'make a raw call to any Meta Graph API endpoint' with a 'configured access token.' It immediately distinguishes itself from the high-level FB/IG sibling tools by labeling itself an 'Advanced/escape hatch.'

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 explicitly directs the agent to use this tool for 'anything the other tools don't cover yet,' which effectively establishes a when-to-use rule. It doesn't enumerate specific sibling alternatives, but the blanket fallback framing is clear enough for an agent to prioritize specialized tools first.

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