Instagram MCP Server

The Instagram MCP Server is a specialized bridge that lets AI assistants like Claude talk directly to Instagram’s Graph API. By exposing a set of model‑controlled tools, application‑controlled resources, and user‑controlled prompts, the server turns a social media account into a first‑class data source and command center. Developers can therefore add real‑time Instagram analytics, content publishing, and engagement insights to their AI workflows without writing custom API wrappers.

At its core, the server solves a common pain point: integrating Instagram’s business features into conversational AI. The platform requires a Facebook‑connected Business account, a long‑lived access token, and several permissions (, , , etc.). Once the credentials are in place, the MCP server automatically translates high‑level requests into Graph API calls. For example, a model can ask for “Get Profile Info” and instantly receive the account’s bio, follower count, and profile picture. Or it can publish a new image by invoking the “Publish Media” tool with minimal boilerplate.

Key capabilities include:

• Tools that let the model fetch profile data, recent posts, post insights, publish media, and list linked Facebook pages.
• Resources such as , , and that the application can expose to multiple models or store for later analysis.
• Prompts pre‑built by the community—like “Analyze Engagement” or “Content Strategy”—which standardize common tasks and reduce the need for custom prompt engineering.

Real‑world use cases span marketing automation, social media management dashboards, and AI‑powered content recommendation engines. A brand could have an assistant that pulls the latest engagement metrics, suggests optimal posting times, and even pushes new creatives directly to Instagram—all within a single conversation. Because the MCP server handles authentication, rate limits, and error handling, developers can focus on business logic rather than API plumbing.

Integrating the server into an AI workflow is straightforward: add the MCP endpoint to your model’s context, choose a tool or resource, and let the assistant orchestrate calls. The server’s modular design means you can expose only the features your application needs, keeping the context lean and secure. Its standout advantage is that it unifies data retrieval and action execution under a single, well‑documented protocol, enabling rapid iteration and reliable production deployments for any developer looking to embed Instagram capabilities into conversational AI.