diff --git a/ai-agents/crew-ai-actions.mdx b/ai-agents/crew-ai-actions.mdx
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@@ -0,0 +1,9 @@
+---
+title: "AI Agent Actions"
+sidebarTitle: "Actions"
+description: "Explore the various actions you can perform with your AI agent in CometChat."
+---
+
+import Actions from '/snippets/ai-agents/actions.mdx';
+
+<Actions />
diff --git a/ai-agents/crew-ai-knowledge-agent.mdx b/ai-agents/crew-ai-knowledge-agent.mdx
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+++ b/ai-agents/crew-ai-knowledge-agent.mdx
@@ -0,0 +1,142 @@
+---
+title: "Build Your Knowledge Agent with CrewAI"
+sidebarTitle: "Knowledge Agent"
+description: "Create a CrewAI knowledge agent that answers from your docs, streams NDJSON to CometChat, and cites sources."
+---
+
+import { Steps, Step } from 'mintlify';
+
+Based on the refreshed [`ai-agent-crew-ai-examples`](https://github.com/cometchat/ai-agent-crew-ai-examples) codebase, here’s how to run the `knowledge_agent` FastAPI service, ingest docs, and stream answers into CometChat.
+
+***
+
+## What you’ll build
+
+- A **CrewAI** agent that grounds replies in your ingested docs (per namespace).
+- A **FastAPI** service with ingest/search/generate endpoints plus a `/stream` SSE.
+- **CometChat AI Agent** wiring that consumes newline-delimited JSON chunks (`text_start`, `text_delta`, `text_end`, `done`).
+
+***
+
+## Prerequisites
+
+- Python 3.10+ with `pip` (or `uv`)
+- `OPENAI_API_KEY` (optionally `OPENAI_BASE_URL`, `KNOWLEDGE_OPENAI_MODEL`, `KNOWLEDGE_EMBEDDING_MODEL`)
+- A CometChat app + AI Agent entry
+
+***
+
+## Run the updated sample
+
+<Steps>
+  <Step title="Install & start">
+    In <code>ai-agent-crew-ai-examples/</code>:
+    <pre><code className="language-bash">python3 -m venv .venv
+source .venv/bin/activate
+pip install -e .
+uvicorn knowledge_agent.main:app --host 0.0.0.0 --port 8000 --reload</code></pre>
+    Env supports <code>.env</code> at repo root or inside <code>knowledge_agent/.env</code>.
+  </Step>
+  <Step title="Set env">
+    <code>OPENAI_API_KEY</code> is required. Optional: <code>OPENAI_BASE_URL</code>, <code>KNOWLEDGE_OPENAI_MODEL</code> (default <code>gpt-4o-mini</code>), <code>KNOWLEDGE_EMBEDDING_MODEL</code> (default <code>text-embedding-3-small</code>).
+  </Step>
+  <Step title="Storage">
+    Ingested files land in <code>knowledge_agent/data/knowledge/&lt;namespace&gt;/</code> and embeddings persist to <code>knowledge_agent/data/chroma/&lt;namespace&gt;/</code>. Duplicate hashes are skipped automatically.
+  </Step>
+</Steps>
+
+***
+
+## API surface (FastAPI)
+
+- `POST /api/tools/ingest` — accept JSON or `multipart/form-data` with `sources` (text/markdown/url) and optional file uploads; returns `saved`, `skipped`, `errors`.
+- `POST /api/tools/searchDocs` — semantic search via Chroma; accepts `namespace`, `query`, `max_results`.
+- `POST /api/agents/knowledge/generate` — single, non-streaming completion (requires at least one message).
+- `POST /stream` — newline-delimited JSON over SSE (`text_start`, `text_delta`, `text_end`, `done`; `error` on failure) ready for CometChat BYOA.
+- Validation/behavior: `/ingest` dedupes by content hash (skips duplicates) and returns `207` when mixed `errors`/`saved`; `/stream` rejects empty `messages`.
+
+### Ingest examples
+
+```bash
+curl -X POST http://localhost:8000/api/tools/ingest \
+  -H "Content-Type: application/json" \
+  -d '{
+        "namespace": "default",
+        "sources": [
+          { "type": "url", "value": "https://docs.crewai.com/" },
+          { "type": "markdown", "title": "Notes", "value": "# CrewAI Rocks" }
+        ]
+      }'
+```
+
+Multipart uploads are also supported:
+
+```bash
+curl -X POST http://localhost:8000/api/tools/ingest \
+  -H "Accept: application/json" \
+  -F "namespace=default" \
+  -F "sources=[{\"type\":\"text\",\"value\":\"Hello\"}]" \
+  -F "files=@/path/to/file.pdf"
+```
+
+### Search + answer
+
+```bash
+curl -X POST http://localhost:8000/api/tools/searchDocs \
+  -H "Content-Type: application/json" \
+  -d '{"namespace":"default","query":"CrewAI agent lifecycle","max_results":4}'
+```
+
+```bash
+curl -N http://localhost:8000/stream \
+  -H "Content-Type: application/json" \
+  -d '{
+        "thread_id": "thread_1",
+        "run_id": "run_001",
+        "messages": [
+          { "role": "user", "content": "Summarize the CrewAI agent lifecycle." }
+        ]
+      }'
+```
+
+Streaming payload shape:
+
+```json
+{"type":"text_start","message_id":"...","thread_id":"...","run_id":"..."}
+{"type":"text_delta","content":"...","message_id":"...","thread_id":"...","run_id":"..."}
+{"type":"text_end","message_id":"...","thread_id":"...","run_id":"..."}
+{"type":"done","thread_id":"...","run_id":"..."}
+# errors (if thrown) look like:
+{"type":"error","message":"...","message_id":"...","thread_id":"...","run_id":"..."}
+```
+
+***
+
+## Crew internals (for reference)
+
+`knowledge_agent/knowledge_manager.py` builds a search tool per namespace, wired into a CrewAI agent:
+
+```python
+search_tool = self._create_search_tool(normalised)
+agent = Agent(
+    role="Knowledge Librarian",
+    goal="Answer user questions with relevant citations from the knowledge base.",
+    tools=[search_tool],
+    llm=model,
+)
+task = Task(
+    description="Use search_knowledge_base before answering.\nConversation: {conversation}\nLatest: {question}",
+    expected_output="A concise, cited answer grounded in ingested docs.",
+    agent=agent,
+)
+crew = Crew(agents=[agent], tasks=[task], process=Process.sequential)
+```
+
+***
+
+## Wire it to CometChat
+
+- Dashboard → **AI Agent → BYO Agents** and then **Get Started / Integrate → Choose CrewAI**. → **Agent ID** (e.g., `knowledge`) → **Deployment URL** = your public `/stream`.
+- The SSE stream is newline-delimited JSON; CometChat AG-UI adapters parse `text_start`/`text_delta`/`text_end` and stop on `done`. Message IDs, thread IDs, and run IDs are included for threading.
+- Use namespaces to keep customer/workspace data separate; pass `namespace` in the payload or inside `tool_params.namespace` (either works; defaults to `default` if omitted).
+- Keep secrets server-side; add auth headers on the FastAPI route if needed.
diff --git a/ai-agents/crew-ai-product-hunt-agent.mdx b/ai-agents/crew-ai-product-hunt-agent.mdx
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index 00000000..7b57387b
--- /dev/null
+++ b/ai-agents/crew-ai-product-hunt-agent.mdx
@@ -0,0 +1,103 @@
+---
+title: "Build a Product Hunt Agent with CrewAI"
+sidebarTitle: "Product Hunt Agent"
+description: "Create a CrewAI agent that fetches Product Hunt posts, answers launch questions, and can trigger frontend actions like confetti."
+---
+
+import { Steps, Step } from 'mintlify';
+
+Refreshed for the latest [`ai-agent-crew-ai-examples`](https://github.com/cometchat/ai-agent-crew-ai-examples) codebase: run the `product_hunt_agent` FastAPI service, wire it to CometChat, and stream SSE updates (with optional confetti actions).
+
+---
+
+## What you’ll build
+
+- A CrewAI agent with tools to **get top posts**, **search**, **timeframes**, and **trigger confetti**.
+- A FastAPI `/stream` endpoint emitting newline-delimited JSON (`text_start`, `text_delta`, `text_end`, `done`).
+- CometChat AI Agent wiring that consumes those SSE chunks; your UI listens for the confetti payload.
+- Streaming events follow `text_start` → `text_delta` chunks → `text_end` → `done` (errors emit `type: "error"`).
+
+---
+
+## Prerequisites
+
+- Python 3.10+ with `pip`
+- `OPENAI_API_KEY` (optionally `OPENAI_BASE_URL`, `PRODUCT_OPENAI_MODEL`)
+- Optional: `PRODUCTHUNT_API_TOKEN` for live GraphQL data (empty lists when missing)
+- CometChat app + AI Agent entry
+
+---
+
+## Run the updated sample
+
+<Steps>
+  <Step title="Install & start">
+    In <code>ai-agent-crew-ai-examples/</code>:
+    <pre><code className="language-bash">python3 -m venv .venv
+source .venv/bin/activate
+pip install -e .
+uvicorn product_hunt_agent.main:app --host 0.0.0.0 --port 8001 --reload</code></pre>
+  </Step>
+  <Step title="Set env">
+    Required: <code>OPENAI_API_KEY</code>. Optional: <code>PRODUCTHUNT_API_TOKEN</code> (GraphQL), <code>PRODUCTHUNT_DEFAULT_TIMEZONE</code> (default <code>America/New_York</code>).
+  </Step>
+</Steps>
+
+***
+
+## API surface (FastAPI)
+
+- `GET /api/top` — top posts by votes (`limit` 1–10).
+- `GET /api/top-week` — rolling window (default 7 days) with `limit` and `days`.
+- `GET /api/top-range` — timeframe queries (`timeframe`, `tz`, `limit`); supports `"today"`, `"yesterday"`, `"last_week"`, `"last_month"`, or ISO dates.
+- `GET /api/search` — Algolia search (`q`, `limit`).
+- `POST /api/chat` — non-streaming CrewAI answer.
+- `POST /stream` — SSE stream (`text_start`, `text_delta`, `text_end`, `done`) ready for CometChat.
+- `POST /api/chat` payload: `{"message": "…", "messages": [{ "role": "user", "content": "…" }]}` (array is required if `message` is omitted).
+
+### Streaming example
+
+```bash
+curl -N http://localhost:8001/stream \
+  -H "Content-Type: application/json" \
+  -d '{
+        "messages": [
+          { "role": "user", "content": "What were the top launches last week?" }
+        ]
+      }'
+```
+
+Streaming payload shape:
+
+```json
+{"type":"text_start","message_id":"...","thread_id":"...","run_id":"..."}
+{"type":"text_delta","content":"...","message_id":"...","thread_id":"...","run_id":"..."}
+{"type":"text_end","message_id":"...","thread_id":"...","run_id":"..."}
+{"type":"done","thread_id":"...","run_id":"..."}
+# errors (when thrown) look like:
+{"type":"error","message":"...","message_id":"...","thread_id":"...","run_id":"..."}
+```
+
+***
+
+## Crew internals (for reference)
+
+Key tools in `product_hunt_agent/agent_builder.py`:
+
+```python
+@tool("getTopProducts")          # votes-ranked, clamps limit 1-10
+@tool("getTopProductsThisWeek")  # rolling-week window, clamps days 1-31 and limit 1-10
+@tool("getTopProductsByTimeframe")  # "today", "yesterday", "last_week", ISO, ranges; clamps limit 1-10
+@tool("searchProducts")          # Algolia search (no token needed)
+@tool("triggerConfetti")         # returns payload: colors, particleCount, spread, startVelocity, origin, ticks, disableSound
+```
+
+All tools run server-side; if `PRODUCTHUNT_API_TOKEN` is missing, top/timeframe queries return empty arrays but still respond cleanly (search still works via Algolia defaults).
+
+***
+
+## Wire it to CometChat
+
+- Dashboard → **AI Agent → BYO Agents** and then **Get Started / Integrate → Choose CrewAI**. → **Agent ID** (e.g., `product_hunt`) → **Deployment URL** = your public `/stream`.
+- Listen for `text_start`/`text_delta`/`text_end` to render streaming text; stop on `done`.
+- When `triggerConfetti` returns, map the payload to your UI handler (Widget/React UI Kit). Keep API tokens server-side.
diff --git a/ai-agents/crew-ai-tools.mdx b/ai-agents/crew-ai-tools.mdx
new file mode 100644
index 00000000..78f2f929
--- /dev/null
+++ b/ai-agents/crew-ai-tools.mdx
@@ -0,0 +1,9 @@
+---
+title: "AI Agent Tools"
+sidebarTitle: "Tools"
+description: "Explore the various tools you can use with your AI agent in CometChat."
+---
+
+import Tools from '/snippets/ai-agents/tools.mdx';
+
+<Tools />
diff --git a/ai-agents/crew-ai.mdx b/ai-agents/crew-ai.mdx
new file mode 100644
index 00000000..a686cbb8
--- /dev/null
+++ b/ai-agents/crew-ai.mdx
@@ -0,0 +1,160 @@
+---
+title: "Create an AI Agent with CrewAI"
+sidebarTitle: "Create AI Agent"
+description: "Connect a CrewAI agent to CometChat, customize it with UI Kit Builder, and ship it as React UI Kit code or a Chat Widget."
+---
+
+import { Steps, Step, CardGroup, Card } from 'mintlify';
+
+## What you’ll build
+
+- A **CrewAI** agent exposed via a public endpoint (e.g., FastAPI `/kickoff`) that streams NDJSON.
+- The same agent **connected to CometChat** (Agent ID + Deployment URL).
+- A **customized chat experience** using **UI Kit Builder**.
+- An export to **React UI Kit code** _or_ **Chat Widget** for integration.
+- A streaming contract that emits `text_start` → `text_delta` → `text_end` → `done` (plus `error`), with `message_id`/`thread_id`/`run_id`.
+
+---
+
+## Prerequisites
+
+- A CometChat account and an app: **[Create App](https://app.cometchat.com/apps)**
+- A CrewAI agent endpoint (Python/FastAPI sample shown below)
+- Python 3.10+ (3.11 recommended) with your preferred package manager (`uv` or `pip`)
+- OpenAI (or Anthropic) API key for the agent
+- Optional service-specific env vars (e.g., Product Hunt token) can live in repo root `.env` or service-level `.env`.
+
+---
+
+## Step 1 - Create your CometChat app
+
+<Steps>
+  <Step title="Create or open an app">
+    Sign in at <b><a href="https://app.cometchat.com/apps">app.cometchat.com</a></b>. Create a new app or open an existing one.
+  </Step>
+  <Step title="Copy credentials">
+    Note your <b>App ID</b>, <b>Region</b>, and <b>Auth Key</b> (needed if you export the Chat Widget later).
+  </Step>
+</Steps>
+
+---
+
+## Step 2 - Connect your CrewAI Agent
+
+Navigate to **AI Agent → BYO Agents** and then **Get Started / Integrate**.
+
+<Steps>
+  <Step title="Choose provider">
+    Select **CrewAI**.
+  </Step>
+  <Step title="Basic details">
+    Provide:
+    <ul>
+      <li><b>Name</b> and optional <b>Icon</b></li>
+      <li>(Optional) <b>Greeting</b> and <b>Introductory Message</b></li>
+      <li>(Optional) <b>Suggested messages</b></li>
+    </ul>
+  </Step>
+  <Step title="CrewAI configuration">
+    Paste:
+    <ul>
+      <li><b>Agent ID</b> — a unique handle that matches how you route traffic (e.g., <code>support</code>).</li>
+      <li><b>Deployment URL</b> — the public HTTPS endpoint exposed by your CrewAI service (e.g., <code>/kickoff</code>).</li>
+      <li>(Optional) <b>Headers</b> — flat JSON auth headers your FastAPI deployment expects.</li>
+    </ul>
+  </Step>
+  <Step title="Save & enable">
+    Click **Save**, then ensure the agent’s toggle is **ON** in **AI Agents** list.
+  </Step>
+</Steps>
+
+> **Tip:** If you update your CrewAI agent later (prompts, tools, routing), you won’t need to re-connect it in CometChat—just keep the **Agent ID** and **Deployment URL** the same.
+
+---
+
+## Step 3 - Define Frontend Actions (Optional)
+
+<Steps>
+  <Step title="Add an action">
+    Go to <b>AI Agent → Actions</b> and click <b>Add</b> to create a frontend action your agent can call (e.g., “Open Product,” “Start Demo,” “Book Slot”).
+  </Step>
+  <Step title="Define fields">
+    Include:
+    <ul>
+      <li><b>Display Name</b> — Shown to users (e.g., “Open Product Page”).</li>
+      <li><b>Execution Text</b> — How the agent describes running it (e.g., “Opening product details for the user.”).</li>
+      <li><b>Name</b> — A unique, code‑friendly key (e.g., <code>open_product</code>).</li>
+      <li><b>Description</b> — What the tool does and when to use it.</li>
+      <li><b>Parameters</b> — JSON Schema describing inputs (the agent will fill these).</li>
+    </ul>
+  </Step>
+  <Step title="Validate inputs (schema)">
+    Example parameters JSON:
+
+```json
+{
+  "type": "object",
+  "required": ["productId"],
+  "properties": {
+    "productId": {
+      "type": "string",
+      "description": "The internal product ID to open"
+    },
+    "utm": {
+      "type": "string",
+      "description": "Optional tracking code"
+    }
+  }
+}
+```
+  </Step>
+  <Step title="Handle in your UI">
+    At runtime, listen for tool calls and execute them client‑side (e.g., route changes, modals, highlights).
+  </Step>
+</Steps>
+
+---
+
+## Step 4 - Customize in UI Kit Builder
+<Steps>
+  <Step title="Open variant">From <b>AI Agents</b> click the variant (or Get Started) to enter UI Kit Builder.</Step>
+  <Step title="Customize & Deploy">Select <b>Customize and Deploy</b>.</Step>
+  <Step title="Adjust settings">Theme, layout, features; ensure the CrewAI agent is attached.</Step>
+  <Step title="Preview">Use live preview to validate responses & any tool triggers.</Step>
+</Steps>
+
+<CardGroup>
+  <Card title="Widget Builder" icon={<img src="/docs/images/icons/ai-agents.svg" alt="Widget" />} description="Embed / script" href="/ai-agents/chat-widget" horizontal />
+  <Card title="React UI Kit" icon={<img src="/docs/images/icons/react.svg" alt="React" />} href="https://www.cometchat.com/docs/ui-kit/react/ai-assistant-chat" horizontal>Pre Built UI Components</Card>
+</CardGroup>
+
+---
+
+## Step 5 - Export & Integrate
+
+Choose how you’ll ship the experience (Widget or React UI Kit export).
+
+<Steps>
+  <Step title="Decide delivery mode">Pick <b>Chat Widget</b> (fastest) or export <b>React UI Kit</b> for code-level customization.</Step>
+  <Step title="Widget path">Open <b>UI Kit Builder</b> → Get Embedded Code → copy script + credentials.</Step>
+  <Step title="React UI Kit path">Export the variant as code (UI Kit) if you need deep theming or custom logic.</Step>
+  <Step title="Verify agent inclusion">Preview: the CrewAI agent should appear without extra config.</Step>
+</Steps>
+
+---
+
+## Step 6 - Deploy & Secure (Reference)
+
+If you need a starter CrewAI endpoint, you can reuse the `/kickoff` pattern from your CrewAI project. Stream newline-delimited JSON events in this order: `text_start` → `text_delta` chunks → `text_end` → `done` (emit `error` on failures). Include `message_id` plus optional `thread_id` and `run_id` for threading.
+
+```python
+@app.post("/kickoff")
+async def kickoff(request: KickoffRequest):
+  inputs = {
+    "user_message": request.messages[-1].content,
+    "conversation_history": "\n".join([f"{m.role}: {m.content}" for m in request.messages[:-1]]),
+  }
+  return StreamingResponse(stream_crew(inputs), media_type="application/x-ndjson")
+```
+
+Deploy behind HTTPS, add auth headers, and keep API keys server-side. Once live, update your CometChat agent’s **Deployment URL** to point at the public endpoint and keep the toggle **ON**.
\ No newline at end of file
diff --git a/docs.json b/docs.json
index 2ccdf8f0..3404abbc 100644
--- a/docs.json
+++ b/docs.json
@@ -4870,6 +4870,27 @@
                   }
                 ]
               },
+              {
+                "dropdown": "CrewAI",
+                "icon": "/images/icons/crew-ai.svg",
+                "pages": [
+                  "/ai-agents/crew-ai",
+                  "/ai-agents/crew-ai-actions",
+                  "/ai-agents/crew-ai-tools",
+                  {
+                    "group": "Guides",
+                    "pages": [
+                      "/ai-agents/crew-ai-knowledge-agent"
+                    ]
+                  },
+                  {
+                    "group": "Tutorials",
+                    "pages": [
+                      "/ai-agents/crew-ai-product-hunt-agent"
+                    ]
+                  }
+                ]
+              },
               {
                 "dropdown": "Agno",
                 "icon": "/images/icons/agno.svg",