Sync open source content 🐝 (from b90fd66c2b897ae8dc9bd1739f0529a607bcc5ba)

Author: beezythebot

_meta.global.tsx

@@ -44,13 +44,21 @@ const meta = {
         display: "children",
         items: {
           introduction: {
-            title: "Intro",
+            title: "Introduction",
           },
-          "gram-quickstart": {
-            title: "Quickstart",
+          "mcp-installation-guides": {
+            title: "MCP Installation Guides",
           },
-          guides: {
-            title: "Guides",
+          "getting-started": {
+            title: "Getting Started",
+            items: {
+              typescript: {
+                title: "Use TypeScript",
+              },
+              openapi: {
+                title: "Use an OpenAPI Spec",
+              },
+            },
           },
           concepts: {
             title: "Concepts",

docs/gram/api-clients/using-anthropic-api-with-gram-mcp-servers.mdx

@@ -5,7 +5,7 @@ sidebar:
   order: 2
 ---
 
-Anthropic's [Messages API](https://docs.anthropic.com/en/api/messages) supports remote MCP servers through their MCP connector feature. This allows you to give Claude models direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/gram-quickstart).
+Anthropic's [Messages API](https://docs.anthropic.com/en/api/messages) supports remote MCP servers through their MCP connector feature. This allows you to give Claude models direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/quickstart).
 
 This guide will show you how to connect Anthropic's API to a Gram-hosted MCP server using an example [Push Advisor API](https://github.com/ritza-co/gram-examples/blob/main/push-advisor-api/openapi.yaml). You'll learn how to create an MCP server from an OpenAPI document, set up the connection, configure authentication, and use natural language to query the example API.
 
@@ -60,7 +60,6 @@ Click **Toolsets** in the sidebar to view the Push Advisor toolset.
 
 ![Screenshot of the Gram dashboard showing the Push Advisor toolset](/assets/docs/gram/img/guides/mcp-installing-ide/toolset-created.png)
 
-
 ### Publishing an MCP server
 
 Let's make the toolset available as an MCP server.
@@ -310,13 +309,13 @@ try:
         ],
         betas=["mcp-client-2025-04-04"]
     )
-    
+
     # Check for MCP tool errors in the response
     for content in response.content:
         if hasattr(content, 'type') and content.type == 'mcp_tool_result':
             if hasattr(content, 'is_error') and content.is_error:
                 print(f"Tool error occurred: {content}")
-    
+
     print(response.content[0].text)
 except Exception as error:
     print(f"API call failed: {error}")
@@ -384,7 +383,6 @@ Click **Connect** to establish a connection to your MCP server.
 
 Use the Inspector to verify that your MCP server responds correctly before integrating it with your Anthropic API calls.
 
-
 ## What's next
 
 You now have Anthropic's Claude models connected to your Gram-hosted MCP server, giving them access to your custom APIs and tools.

docs/gram/api-clients/using-langchain-with-gram-mcp-servers.mdx

@@ -5,7 +5,7 @@ sidebar:
   order: 4
 ---
 
-[LangChain](https://www.langchain.com/) and [LangGraph](https://www.langchain.com/langgraph) support MCP servers through the `langchain-mcp-adapters` library, which allows you to give your LangChain agents and LangGraph workflows direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/gram-quickstart).
+[LangChain](https://www.langchain.com/) and [LangGraph](https://www.langchain.com/langgraph) support MCP servers through the `langchain-mcp-adapters` library, which allows you to give your LangChain agents and LangGraph workflows direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/quickstart).
 
 This guide demonstrates how to connect LangChain to a Gram-hosted MCP server using an example [Push Advisor API](https://github.com/ritza-co/gram-examples/blob/main/push-advisor-api/openapi.yaml). You'll learn how to create an MCP server from an OpenAPI document, set up the connection, configure authentication, and use natural language to query the example API.
 

docs/gram/api-clients/using-openai-agents-sdk-with-gram-mcp-servers.mdx

@@ -7,7 +7,7 @@ import { Callout } from "@/mdx/components";
 
 The OpenAI [Agents SDK](https://openai.github.io/openai-agents-python/) is a production-ready framework for building agentic AI applications. The Agents SDK provides advanced features like persistent sessions, agent handoffs, guardrails, and comprehensive tracing for complex workflows.
 
-When combined with [Gram-hosted MCP servers](/docs/gram/gram-quickstart), the Agents SDK enables you to build sophisticated agents that can interact with your APIs, databases, and other services through natural language conversations with persistent context.
+When combined with [Gram-hosted MCP servers](/docs/gram/quickstart), the Agents SDK enables you to build sophisticated agents that can interact with your APIs, databases, and other services through natural language conversations with persistent context.
 
 This guide shows you how to connect the OpenAI Agents SDK to a Gram-hosted MCP server using Taskmaster, a full-stack CRUD application for task and project management. Taskmaster includes a web UI for managing projects and tasks, a built-in HTTP API, OAuth 2.0 authentication, and a Neon PostgreSQL database for storing data. Try the [demo app](https://taskmaster-speakeasyapi.vercel.app/) to see it in action.
 
@@ -34,7 +34,7 @@ To follow this tutorial, you need:
 
 ## Creating a Taskmaster MCP server
 
-Before connecting the OpenAI Agents SDK to a Taskmaster MCP server, you first need to create one. 
+Before connecting the OpenAI Agents SDK to a Taskmaster MCP server, you first need to create one.
 
 Follow the guide to [creating a Taskmaster MCP server](/docs/gram/examples/creating-taskmaster-mcp-server), which walks you through:
 
@@ -66,7 +66,10 @@ export GRAM_KEY=your-gram-api-key  # Optional: only needed for private MCP serve
 ```
 
 <Callout title="Code Examples" type="info">
-Throughout this guide, replace `your-taskmaster-slug` with your actual MCP server URL and update the header names to match your server configuration from the guide to [creating a Taskmaster MCP server](/docs/gram/examples/creating-taskmaster-mcp-server).
+  Throughout this guide, replace `your-taskmaster-slug` with your actual MCP
+  server URL and update the header names to match your server configuration from
+  the guide to [creating a Taskmaster MCP
+  server](/docs/gram/examples/creating-taskmaster-mcp-server).
 </Callout>
 
 ### Basic connection (public server)
@@ -397,8 +400,8 @@ When the browser opens:
 - In the **Transport Type** field, select **Streamable HTTP** (not the default stdio).
 - Enter your server URL: `https://app.getgram.ai/mcp/your-taskmaster-slug`.
 - For authentication, add **API Token Authentication**:
-     - **Header name:** `MCP-TASKMASTER-API-KEY`
-     - **Bearer token:** Your Taskmaster API key
+  - **Header name:** `MCP-TASKMASTER-API-KEY`
+  - **Bearer token:** Your Taskmaster API key
 - Click **Connect** to test the connection.
 
 **Note:** Taskmaster servers use custom authentication headers that may not be fully supported by the standard MCP Inspector interface. For guaranteed testing, use the Gram Playground or the code examples in this guide.

docs/gram/api-clients/using-openai-api-with-gram-mcp-servers.mdx

@@ -5,7 +5,7 @@ sidebar:
   order: 1
 ---
 
-The OpenAI [Responses API](https://platform.openai.com/docs/api-reference/responses) supports remote MCP servers through its MCP tool feature. This allows you to give GPT models direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/gram-quickstart).
+The OpenAI [Responses API](https://platform.openai.com/docs/api-reference/responses) supports remote MCP servers through its MCP tool feature. This allows you to give GPT models direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/getting-started).
 
 This guide shows you how to connect the OpenAI Responses API to a Gram-hosted MCP server using an example [Push Advisor API](https://github.com/ritza-co/gram-examples/blob/main/push-advisor-api/openapi.yaml). You'll learn how to create an MCP server from an OpenAPI document, set up the connection, configure authentication, and use natural language to query the example API.
 
@@ -190,17 +190,17 @@ If your Gram MCP server has multiple tools but you only want to expose certain o
 
 ```javascript
 const response = await client.responses.create({
-    model: "gpt-4.1",
-    tools: [
-        {
-            type: "mcp",
-            server_label: "gram-pushadvisor",
-            server_url: "https://app.getgram.ai/mcp/canipushtoprod",
-            allowed_tools: ["can_i_push_to_prod"],
-            require_approval: "never",
-        },
-    ],
-    input: "Is it safe to deploy today?",
+  model: "gpt-4.1",
+  tools: [
+    {
+      type: "mcp",
+      server_label: "gram-pushadvisor",
+      server_url: "https://app.getgram.ai/mcp/canipushtoprod",
+      allowed_tools: ["can_i_push_to_prod"],
+      require_approval: "never",
+    },
+  ],
+  input: "Is it safe to deploy today?",
 });
 ```
 
@@ -389,4 +389,4 @@ Use the Inspector to verify that your MCP server responds correctly before integ
 
 You now have OpenAI's GPT models connected to your Gram-hosted MCP server, giving them access to your custom APIs and tools.
 
-Ready to build your own MCP server? [Try Gram today](/product/gram) and see how easy it is to turn any API into agent-ready tools that work with both OpenAI and Anthropic models.
+Ready to build your own MCP server? [Try Gram today](/product/gram) and see how easy it is to turn any API into agent-ready tools that work with both OpenAI and Anthropic models.

docs/gram/api-clients/using-pydantic-ai-with-gram-mcp-servers.mdx

@@ -5,7 +5,7 @@ sidebar:
   order: 5
 ---
 
-[Pydantic AI](https://ai.pydantic.dev/) supports MCP servers through the `pydantic-ai-mcp-client` library. This allows you to give your Pydantic AI agents direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/gram-quickstart).
+[Pydantic AI](https://ai.pydantic.dev/) supports MCP servers through the `pydantic-ai-mcp-client` library. This allows you to give your Pydantic AI agents direct access to your tools and infrastructure by connecting to [Gram-hosted MCP servers](/docs/gram/quickstart).
 
 This guide shows you how to connect Pydantic AI to a Gram-hosted MCP server using an example [Push Advisor API](https://github.com/ritza-co/gram-examples/blob/main/push-advisor-api/openapi.yaml). You'll learn how to create an MCP server from an OpenAPI document, set up the connection, configure authentication, and use natural language to query the example API.