wazap-mcp

List WhatsApp chats

list_chats

Read-onlyIdempotent

Retrieve active WhatsApp conversations sorted by recent activity to find a chat_id, with details like unread count and last message.

Instructions

Conversations, most recently active first: chat_id, name, type, unread count, last message, and whether archived, pinned, muted or left. Use it to find a chat_id.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`limit`	No
`filter`	No	"all" leaves out archived	all
`account_id`	No	Account id

Output Schema

TableJSON Schema

Name	Required	Description	Default
`sync`	Yes
`chats`	Yes
`count`	Yes
`filter`	Yes
`account_id`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

Changed4 schema fields changedv1.0.3Sep 23, 2026

changedInput schema / properties / account_id / description

Previous value: -"Registry account id (default, work, …). Omit to resolve from chat_id or message_id, or the default account."New value: +"Account id"

changedInput schema / properties / filter / description

Previous value: -"Which chats to list; \"all\" (default) excludes archived ones"New value: +"\"all\" leaves out archived"

removedInput schema / properties / limit / description
```
Removed value: -"Maximum number of chats (1-100)"
```

changedOutput schema / (root)

Previous value: -nullNew value: +{
+  "$schema": "http://json-schema.org/draft-07/schema#",
+  "additionalProperties": false,
+  "properties": {
+    "account_id": {
+      "type": "string"
+    },
+    "chats": {
+      "items": {
+        "additionalProperties": true,
+        "properties": {
+          "chat_id": {
+            "type": "string"
+          },
+          "last_message": {
+            "anyOf": [
+              {
+                "additionalProperties": true,
+                "properties": {
+                  "private": {
+                    "const": true,
+                    "description": "Tagged #private: no words",
+                    "type": "boolean"
+                  }
+                },
+                "type": "object"
+              },
+              {
+                "type": "null"
+              }
+            ]
+          },
+          "name": {
+            "type": "string"
+          },
+          "type": {
+            "type": "string"
+          },
+          "unread_count": {
+            "type": "number"
+          }
+        },
+        "required": [
+          "chat_id",
+          "name",
+          "type",
+          "unread_count"
+        ],
+        "type": "object"
+      },
+      "type": "array"
+    },
+    "count": {
+      "type": "number"
+    },
+    "filter": {
+      "type": "string"
+    },
+    "sync": {
+      "type": "string"
+    }
+  },
+  "required": [
+    "filter",
+    "count",
+    "chats",
+    "sync",
+    "account_id"
+  ],
+  "type": "object"
+}

Changed1 schema field changedv0.15.0Sep 12, 2026

addedInput schema / properties / account_id

Added value: +{
+  "description": "Registry account id (default, work, …). Omit to resolve from chat_id or message_id, or the default account.",
+  "minLength": 1,
+  "type": "string"
+}

First observedv0.9.3Aug 23, 2026

TDQS

A4.3/5.0

Behavior4/5

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

The description adds behavioral context beyond the annotations by disclosing sort order ('most recently active first') and the chat states surfaced (archived, pinned, muted, left). The annotations already cover read-only, idempotent, and non-destructive behavior, lowering the burden on the description.

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?

The description is two sentences with no filler: the first front-loads the key ordering and return fields, and the second gives the direct use case. Every word earns its place.

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 low-complexity, read-only list tool, the combination of this description, the rich annotations, and the output schema gives an agent everything needed to call it correctly. No necessary prerequisites, return-value details, or edge behaviors are 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 description itself adds little about limit, filter, or account_id. However, the schema already documents filter and account_id with descriptions, and limit has clear bounds and a default, so the parameter meaning is adequately covered without the description compensating further.

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 opens with a specific outcome—'Conversations, most recently active first'—and enumerates the exact fields returned: chat_id, name, type, unread count, last message, and archived/pinned/muted/left state. It closes with a concrete intended use ('Use it to find a chat_id'), which clearly distinguishes it from the messaging and management siblings.

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 states a clear use case: finding a chat_id. It does not name sibling alternatives or explain when not to use it, so it stops short of full routing guidance, but the context is clear enough for an agent to select it appropriately.

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