Provides read-only tools to access WhatsApp history and attachments from a local archive, including chat enumeration, message history with deterministic pagination, and retrieval of approved attachment bytes.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type @ followed by the MCP server name and your instructions, e.g., "@WhatsApp Read Agent MCP Server Get the last 10 messages from Rajesh Aggarwal"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
Strictly read-only access to your own WhatsApp history and attachments, for an AI assistant (via the Model Context Protocol) or any script that reads the local archive.
It is built so that reading and writing are physically separated:
Component | Talks to WhatsApp? | What it can do |
Collector ( | Yes — links a companion device | Receives history sync + new messages, downloads attachments under a size cap. Nothing else. |
MCP server ( | No | Reads the local archive only. Enumerate chats, page history deterministically, read exact timestamps/content, return approved attachment bytes. |
The MCP server has no code path to send, reply, react, call, archive, delete, mark-read,
pay, or transfer — those tools are not registered and the WhatsApp socket is not even
imported into that process. src/server.test.ts asserts the tool surface is exactly the
seven read-only tools, so a mutating tool cannot be added without a test failing.
This is unofficial. It links a companion device using the multi-device protocol
(via @whiskeysockets/baileys), the same
mechanism as WhatsApp Web, but programmatically. This is not an official WhatsApp API
and may violate WhatsApp's Terms of Service. Automating a client can get the account
banned. There is no sanctioned API that exposes personal 1:1/group history — the
official WhatsApp Cloud API only handles messages to a registered business number. Use
this only on your own account, understanding that risk.
Everything derived from a linked account stays local and gitignored: companion-device
credentials (auth/), the message archive (data/), and downloaded media (media/).
Never commit them. The device credentials grant full account access — treat them like a
password.
Attachment downloads are double-gated: an explicit per-message approval flag and an optional operator allowlist of chat JIDs. The MCP server only ever surfaces bytes the collector already downloaded; it never reaches out to WhatsApp to fetch anything.
Related MCP server: WhatsApp MCP Server
cd whatsapp-agent
npm install # MCP SDK + zod (Baileys is an optional dep, see below)
npm run check # build + 31 unit/integration tests (no device or network needed)The pure read model, deterministic pagination, consent gate, and path-safety checks are all covered by tests that run offline. The collector's WhatsApp handling requires a live device and cannot be exercised in CI.
The collector needs the optional dependency:
npm install @whiskeysockets/baileys qrcode-terminal
cp .env.example .env # adjust paths / limits if desired
npm run collect # prints a QR (or a pairing code if WHATSAPP_PAIR_NUMBER is set)On your phone: WhatsApp → Settings → Linked devices → Link a device, then scan the QR
(or choose "Link with phone number" and enter the printed pairing code). The collector then
receives the history sync and writes it to data/ (and attachments to media/). Keep it
running to keep the archive current. Re-run it anytime to resume.
Build first (npm run build), then point your MCP host at the built entry:
{
"mcpServers": {
"whatsapp-read": {
"command": "node",
"args": ["/absolute/path/to/rs-website-firebase/whatsapp-agent/dist/index.js"],
"env": {
"WHATSAPP_DATA_DIR": "/absolute/path/to/whatsapp-agent/data",
"WHATSAPP_MEDIA_DIR": "/absolute/path/to/whatsapp-agent/media",
"WHATSAPP_ATTACHMENT_ALLOWLIST": ""
}
}
}
}The server loads the archive at startup. After a fresh sync, restart it to pick up new messages.
Tool | Purpose |
| Is a device linked, when it last synced, how many chats/messages archived. |
| Enumerate chats (name-ordered, paginated). |
| Locate a named contact or group. |
| Deterministic page of a chat's history; |
| A single message with exact timestamp and content. |
| Messages in a chat that carry attachments. |
| Return an approved attachment's local bytes ( |
Cursors are opaque — pass them back verbatim.
The task's acceptance test ("prove complete readback against Anuj Kapoor and Rajesh Aggarwal") requires a linked device and therefore must be run on a machine with the phone available:
npm run collect and link the device; wait for get_sync_status to report a non-zero
messageCount and stable lastSyncAt.
Start the MCP server (or use the archive directly).
find_chats_by_name → "Anuj Kapoor", then "Rajesh Aggarwal" to get each chat JID.
get_history with direction: "forward", paging on nextCursor until hasMore is
false — that is the complete, ordered history with exact isoTime timestamps.
For any attachment, list_attachments then get_attachment with approved: true.
The deterministic pagination and the end-to-end "locate named chat → page complete history"
flow are proven in src/read-api.test.ts and src/server.test.ts against seeded Anuj/Rajesh
fixtures. The live readback against the real account was not run here: this
environment is headless (no phone to scan the QR, no persistent host), so a device cannot be
linked from it. Run steps 1–5 on your own machine to complete the acceptance test.
Find chats whose resolved name matches (case-insensitive substring). Use this to locate a named contact or group, e.g. before reading their full history.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Contact or group name to search for. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the burden of behavioral disclosure. It adds value by disclosing that matching is case-insensitive and substring-based, and that it operates on 'resolved names' – a useful nuance. For a search tool, this is adequate; it doesn’t explicitly state read-only, but 'Find' implies it. Missing details like pagination or result limits are not critical for such a simple query.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences: the first states the core functionality, the second gives a practical use case. There is no wordy filler or redundancy, and the most important information is front-loaded. Every sentence earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With a single parameter, no output schema, and simple search behavior, the description is mostly complete. It explains the search semantics and gives a typical use case tied to a sibling tool (get_history). It does not mention potential multi-word handling or result limits, but these are minor gaps given the tool's simplicity and sibling context.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has one parameter 'name' with a description ('Contact or group name to search for'), giving 100% schema coverage. The tool description adds semantic value by explaining how 'name' is used: it matches against the 'resolved name' as a case-insensitive substring. This goes beyond the schema and helps the agent understand the matching behavior.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with 'Find chats whose resolved name matches (case-insensitive substring)', which is a specific verb ('Find'), resource ('chats'), and qualifier ('by name'). This clearly distinguishes it from sibling tools like list_chats, which would list all chats, and get_history/get_message, which target individual chats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly tells the agent when to use this tool: 'Use this to locate a named contact or group, e.g., before reading their full history.' This provides a clear use case and a workflow hint (use before get_history). It does not explicitly state when not to use it or name alternatives, but the guidance is sufficient for most scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Return an approved attachment's locally-archived bytes. Requires approved: true for the specific message (and passes the operator allowlist, if configured). Never fetches from WhatsApp — only surfaces bytes the collector already downloaded.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| chatId | Yes | ||
| approved | Yes | Must be true to release the bytes — explicit per-message approval. | |
| includeBase64 | No | If true, include base64 bytes inline; otherwise return the local path only. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly reveals that the tool only returns locally-archived bytes, never fetches from WhatsApp, requires explicit per-message approval, and is subject to an operator allowlist. These are meaningful behavioral traits that go beyond the input schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the primary action, and every clause contributes meaning (approval requirement, no network fetch, local-only). There is no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The tool is simple with 4 parameters and no output schema. The description covers the essential preconditions (approval, allowlist) and core behavior (local-only, no fetch), which is sufficient for an agent to decide when to invoke it. However, the exact return format (inline base64 vs. local path) is only implied through the includeBase64 parameter, not spelled out in the description.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema already provides descriptions for 'approved' and 'includeBase64', covering half the parameters. The description reinforces the requirement for 'approved' but does not explain 'id' or 'chatId' beyond their self-evident names. Since schema coverage is exactly 50%, not 'low', the baseline of 3 is appropriate; the description adds minimal extra parameter meaning.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb ('Return') and a precise resource ('an approved attachment's locally-archived bytes'), clearly distinguishing it from siblings like list_attachments (which only lists) and get_message (which retrieves messages). The scope is further clarified by 'approved', 'local', and 'Never fetches from WhatsApp'.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description states the key precondition ('Requires approved: true') and mentions the operator allowlist, giving clear context for when the tool can be invoked. It also implies that this tool is for already-downloaded data ('Never fetches from WhatsApp'), but it does not explicitly name sibling alternatives like list_attachments for finding attachment IDs, so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Read a deterministic page of a chat's message history. direction "forward" reads oldest→newest; "backward" scrolls up (newest→oldest). Returned messages are always chronological; pass the cursor back to continue. Iterate until hasMore is false for complete readback.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| chatId | Yes | Chat JID, e.g. 14155551234@s.whatsapp.net or …@g.us. | |
| cursor | No | ||
| direction | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure. It fully explains the deterministic page behavior, direction ordering, chronological return, cursor usage, and termination condition (hasMore). No safety or side-effect warnings are needed since this is read-only, and the pagination contract is described in detail.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, immediately stating the core purpose, followed by essential pagination mechanics. Every sentence adds value; no redundant or filler content. Front-loaded and highly efficient.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a paginated history tool with no output schema, the description covers the key usage contract: page ordering, direction, cursor, and termination. It does not describe the message object fields, but this is likely inferable from siblings like get_message and is secondary to the pagination mechanics. The description is contextually sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description covers only chatId (25%). The description compensates by explaining direction and cursor semantics explicitly ('forward reads oldest→newest', 'pass the cursor back to continue'), which are non-obvious parameters. It does not describe 'limit' but that is self-explanatory. Overall, the description adds significant meaning beyond the schema for the critical parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool reads a page of chat history with a specific verb ('Read') and resource ('chat's message history'). It distinguishes from siblings like get_message by focusing on paginated history and explicitly describes direction semantics (forward/backward), which no other sibling covers.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear operational guidance: how to use direction and cursor, that messages are chronological, and to iterate until hasMore is false. It does not explicitly compare to alternatives (e.g., get_message for single messages), but the sibling names and context make the distinction obvious. Strong usage instructions, but lacked explicit 'when-not-to-use'.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Fetch a single archived message by chat JID and message id, with exact timestamp and content.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | ||
| chatId | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description states it returns exact timestamp and content, adding behavioral context. It also indicates an archived, read-only operation. However, with no annotations, it does not disclose potential outcomes like message not found or error handling, making it adequate but not rich.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence with no redundancy. Every word contributes: the verb, the resource, the identifiers, and the returned data. Well front-loaded for quick scanning.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple fetch operation, the description covers the core purpose, identification parameters, and return value. It lacks details on failure behavior or response structure, but given the tool's simplicity and sibling context, it is fairly complete.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Since schema description coverage is 0%, the description compensates by clarifying that chatId is a chat JID and id is a message id, adding meaning beyond plain string type declarations. It also implies their role in locating the message, though format specifics are absent.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'Fetch' and identifies the resource as a 'single archived message' with the exact identifiers (chat JID and message id). This clearly distinguishes it from siblings like get_history (multiple messages) and get_attachment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The context is clear: use this to fetch one specific archived message by its chat and message IDs. It does not explicitly mention when not to use it or name alternatives, but the single-message phrasing makes the intended use obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Report the local archive status: whether a device is linked, when it last synced, and how many chats/messages are archived. Reads nothing from WhatsApp.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of disclosing behavior. It explicitly states 'Reads nothing from WhatsApp', which informs the agent that this is a safe, local read operation with no network or write side effects. It does not cover edge cases like unlinked devices, but the core behavioral trait is disclosed.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two concise sentences. The first sentence front-loads the purpose with 'Report', lists key output fields, and the second adds a valuable safety qualifier. Every word earns its place with no redundancy or fluff.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a zero-parameter tool with no output schema, the description fully specifies what the tool returns: link status, last sync time, and archive counts. It also clarifies the local nature of the data. There is no additional complexity requiring more context, making the description complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline score is 4. The description adds no parameter info because there are none to explain. The schema coverage is effectively 100% since the input schema is empty, so no additional meaning is needed beyond what the schema already conveys.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Report' and clearly identifies the resource as 'the local archive status'. It lists the exact pieces of information provided (linked device, last sync time, counts of archived chats/messages), which differentiates it from sibling tools that access individual chats, messages, or attachments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies a clear use case: when an AI agent needs to know the sync/link status or archive counts. It does not explicitly name alternatives or exclusions, but the contrast with sibling tools (list_chats, get_message, etc.) is implicit and sufficient for a simple status query tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List archived messages in a chat that carry an attachment (image/video/audio/document/sticker), with metadata and whether bytes are downloaded. Deterministic forward pagination.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| chatId | Yes | ||
| cursor | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the burden and does disclose some behavioral traits: it lists metadata, indicates whether bytes are downloaded, and notes 'deterministic forward pagination'. However, it does not mention read-only status, auth requirements, or what 'archived' means, leaving gaps in behavioral coverage.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the primary purpose and followed by a succinct pagination note. Every word earns its place, with no redundant phrasing.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a list tool with 3 parameters and no output schema, the description is reasonably complete: it defines scope, includes metadata details, and specifies pagination behavior. It could add return shape or error conditions, but given the simplicity, it is adequate and slightly above minimum.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 0%, so the description must compensate. It mentions pagination but does not explain the limit, cursor, or chatId parameters beyond what the schema already shows. This is a significant gap given there are three parameters, only one of which is required.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb 'List' with a clear resource ('archived messages in a chat that carry an attachment') and enumerates attachment types. It clearly distinguishes from sibling tools like get_attachment (which likely fetches a single attachment) and get_history (which lists messages generally).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
It states the tool is for listing chat messages with attachments, which provides clear context for when to use it. However, it does not explicitly contrast with alternatives or state when not to use it, so it misses the 'explicit alternatives' bar for a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
List archived chats (1:1 and group), ordered deterministically by name. Optionally filter by a name substring. Paginate with the returned cursor.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | ||
| cursor | No | Opaque cursor from a previous page; pass verbatim. | |
| search | No | Case-insensitive substring to filter chat names. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the transparency burden. It discloses deterministic ordering, optional filtering, and cursor-based pagination, which are key behavioral traits. It does not cover auth, rate limits, or return format, but for a simple read-only listing tool, the disclosed behaviors are adequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise: two sentences, front-loaded with the primary purpose, and every clause adds value. No redundant phrasing or excessive detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple list tool with no output schema and no annotations, the description covers the essential operational aspects: what is listed, ordering, optional filter, and pagination. It does not describe the return item structure, but the tool's simplicity makes this a minor gap rather than a critical omission.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 67% (2 of 3 parameters have descriptions). The description adds some context by linking 'search' to 'name substring' and explaining cursor pagination, but it does not add meaning for the 'limit' parameter beyond its schema constraints. This aligns with the baseline score of 3 for adequate schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('List'), the resource ('archived chats'), and the scope ('1:1 and group'), and adds a distinctive behavioral detail ('ordered deterministically by name'). This distinguishes it from sibling tools like find_chats_by_name, which likely searches non-archived chats.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool: it lists archived chats, supports optional name substring filtering, and explains pagination via cursor. It does not explicitly mention alternatives or exclusions, but the specification of 'archived' and the pagination method offer enough guidance for correct use.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
v1.0.0find_chats_by_nameget_attachmentget_historyget_messageget_sync_statuslist_attachmentslist_chatsScored across 7 tools
Most tools are distinct, but list_chats and find_chats_by_name overlap since list_chats already supports name-substring filtering. This could confuse an agent choosing between them, though descriptions help clarify the intended use case.
Tool names consistently follow a verb_noun pattern with lowercase and underscores. Minor deviation: list_chats vs find_chats_by_name for similar operations, but overall the pattern is readable and predictable.
Seven tools is well-scoped for a read-only WhatsApp archive agent. Each tool covers a specific aspect (sync status, chat listing, history, single messages, attachments), and none feel redundant or missing at this scale.
The tool set provides full coverage for reading archived WhatsApp data: sync status, chat discovery, full message history retrieval, individual message access, and attachment handling. No significant operations are missing for the stated purpose of a read agent.
WhatsApp for your app or AI agent over OAuth2 — the same connections WASync runs inside your CRM.
WhatsApp CRM for AI agents: search contacts, read chats, manage the sales pipeline, send messages.
Give your AI agents a real WhatsApp number to send and receive messages.
Run WhatsApp Business campaigns from any AI assistant: contacts, segments, and broadcasts.
