diff --git a/docs/integrations/assets/wolfram.svg b/docs/integrations/assets/wolfram.svg
new file mode 100644
index 0000000000..08a7d44910
--- /dev/null
+++ b/docs/integrations/assets/wolfram.svg
@@ -0,0 +1,12 @@
+
+
\ No newline at end of file
diff --git a/docs/integrations/wolfram.md b/docs/integrations/wolfram.md
new file mode 100644
index 0000000000..f9a2f23410
--- /dev/null
+++ b/docs/integrations/wolfram.md
@@ -0,0 +1,100 @@
+---
+catalog_title: Wolfram
+catalog_description: Inject precise, real-time computation and knowledge
+catalog_icon: /integrations/assets/wolfram.svg
+catalog_tags: ["data", "mcp"]
+---
+
+# Wolfram MCP tool for ADK
+
+
+ Supported in ADKPythonTypeScript
+
+
+The [Wolfram MCP Server](https://www.wolfram.com/artificial-intelligence/mcp-service/)
+transforms your AI environment into a rigorous computational powerhouse. By
+integrating [Wolfram Language](https://www.wolfram.com/language/) and
+[Wolfram|Alpha](https://www.wolframalpha.com/), this server provides access to
+curated data and sophisticated algorithms. When a user submits a query, the LLM
+works with Wolfram to convert it into Wolfram Language for precise evaluation,
+and these exact results are incorporated into the response provided by the LLM.
+
+Whether you are solving complex differential equations, analyzing chemical
+structures or querying real-time socioeconomic data, the MCP Server ensures
+your AI has the "computational brain" necessary to deliver verified, high-level
+technical results that can be trusted.
+
+## Use cases
+
+- Solving complex differential equations
+- Analyzing chemical structures
+- Querying real-time socioeconomic data
+
+## Prerequisites
+
+- No special requirements
+- No auth needed
+
+## Use with agent
+
+=== "Python"
+
+ === "Remote MCP Server"
+
+ ```python
+ from google.adk.agents import Agent
+ from google.adk.tools.mcp_tool import McpToolset
+ from google.adk.tools.mcp_tool.mcp_session_manager import StreamableHTTPConnectionParams
+
+ root_agent = Agent(
+ model="gemini-flash-latest",
+ name="wolfram_agent",
+ instruction="Use Wolfram tools for computation and knowledge queries.",
+ tools=[
+ McpToolset(
+ connection_params=StreamableHTTPConnectionParams(
+ url="https://agenttools.wolfram.com/mcp",
+ ),
+ )
+ ],
+ )
+ ```
+
+=== "TypeScript"
+
+ === "Remote MCP Server"
+
+ ```typescript
+ import { LlmAgent, MCPToolset } from "@google/adk";
+
+ const rootAgent = new LlmAgent({
+ model: "gemini-flash-latest",
+ name: "wolfram_agent",
+ instruction: "Use Wolfram tools for computation and knowledge queries.",
+ tools: [
+ new MCPToolset({
+ type: "StreamableHTTPConnectionParams",
+ url: "https://agenttools.wolfram.com/mcp",
+ }),
+ ],
+ });
+
+ export { rootAgent };
+ ```
+
+## Available tools
+
+Tool | Description
+---- | -----------
+`WolframContext` | Uses semantic search to retrieve any relevant information from Wolfram
+`WolframLanguageEvaluator` | Evaluates Wolfram Language code for the user in a Wolfram Language kernel
+`WolframAlpha` | Use natural language queries with Wolfram\|Alpha to get up-to-date computational results about entities in chemistry, physics, geography, history, art, astronomy, and more
+
+These are documented in
+[Wolfram/AgentTools/tutorial/DefaultTools](https://reference.wolfram.com/language/Wolfram/AgentTools/tutorial/DefaultTools.html).
+
+## Additional resources
+
+- [Wolfram MCP Service Documentation](https://www.wolfram.com/artificial-intelligence/mcp-service/)
+- [Wolfram AgentTools Repository](https://github.com/WolframResearch/AgentTools)
+- [Wolfram Support](https://support.wolfram.com/)