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Gonzalez8

whatsapp-business-mcp

by Gonzalez8

wa_api_call

Call WhatsApp Business API endpoints not covered by dedicated tools, using a validated path and method. Works with GET, POST, DELETE against Meta Graph resources like templates, messages, and media.

Instructions

Escape hatch for WhatsApp Business / Meta Graph endpoints that don't have a dedicated tool yet.

Restricted: only paths matching a curated allowlist of WhatsApp Business resources are accepted (message_templates, phone_numbers, messages, media, business_profile, analytics, subscribed_apps, owned_whatsapp_business_accounts, single-ID reads, wamid lookups). Anything else is rejected.

Prefer the typed tools when one matches — they validate inputs and surface clearer errors.

Inputs:

  • path: starts with /, e.g. /{waba_id}/subscribed_apps

  • query_params: raw query string without leading ? (will be appended)

  • body_json: JSON string of the request body, used with POST/DELETE

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pathYesGraph API path starting with /, e.g. /{waba_id}/subscribed_apps
methodYesHTTP method
body_jsonNoJSON string of request body for POST/DELETE
query_paramsNoQuery string params (without leading ?), e.g. fields=id,name&limit=100
Behavior4/5

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

With no annotations, the description carries full burden. It discloses the allowlist restriction and input formatting behavior (query appended, body used for POST/DELETE). However, it does not mention response shape, error behavior, or authentication side effects, which are relevant for a generic API passthrough.

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 well-structured with sections for purpose, restrictions, usage, and inputs. It is slightly long but every sentence adds value, and the front-loaded purpose and restriction are effective.

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 complex generic API tool with 4 parameters and no output schema, the description covers purpose, restrictions, usage guidance, and parameter formats. It lacks explicit statement about return values or error handling, which would make it more complete.

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?

Schema description coverage is 100%, so baseline is 3. The description mostly repeats schema descriptions but adds minor context like 'will be appended' for query_params. It does not significantly enhance parameter understanding beyond the schema.

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 the tool is an 'escape hatch' for WhatsApp Business endpoints lacking dedicated tools, distinguishing it from typed siblings. It lists specific resource categories it covers, making the purpose unambiguous.

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 instructs to 'prefer the typed tools when one matches' and explains why (validation, clearer errors). Also specifies allowed path patterns and rejection of non-allowlisted paths, providing clear when-to-use/when-not-to-use 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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