API Docs

Jasper MCP Server

Connect AI Agents to Jasper for on-brand content creation

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Beta

The Jasper MCP Server is currently in beta for business customers with API access. Production use is supported, but we are actively improving the experience based on feedback. You may experience occasional issues or unexpected behavior.

Overview

Model Context Protocol (MCP) is an open protocol that standardizes how applications provide context and tools to large language models (LLMs).

The Jasper MCP Server defines a set of tools that external AI agents can use to access Jasper IQ—your workspace's contextual layer of brand voices, target audiences, style rules, and knowledge—and Jasper-powered content creation. This enables Jasper customers to maintain brand control across multiple AI platforms, ensuring all AI-generated content consistently stays on-brand and high-quality.

Jasper offers options for both Local and Remote configuration of the MCP.

Available Tools

The Jasper MCP Server offers a subset of API capabilities as tools tailored for AI agents. These tools provide Jasper-powered content creation and read-only access to your workspace's IQ context.

ToolWhat it does
generate-contentCreates content using your configured voices, audiences, style rules, knowledge, and any additional context provided by the connected AI Agent.
get-jasper-brand-voicesRetrieves Jasper brand voices available to the workspace
get-jasper-audiencesRetrieves Jasper brand voices available to the workspace
search-knowledge-baseSearches through the Jasper knowledge base to find relevant documents and information.
get-jasper-style-guidesRetrieves the Jasper style guide configuration available to the workspace.
apply-styleApplies style guide rules to text content and returns the styled content

Local Setup

Local MCP servers run on your machine and connect directly to AI applications. Jasper offers two options for local setup.

Option 1: Desktop Extension (.DXT)

The Desktop Extension offers one-click installation and is accessible for non-technical users. This new format was introduced by Anthropic with support in Claude Desktop. We expect more AI applications to adopt this installation method soon.

1. Download the .DXT file

📥 Download Extension (.DXT)

2. Configure in your MCP Client

See Using Jasper in Claude for example configuration & usage.

Option 2: Install via NPM

For developers looking for a more traditional local server experience, you can install via NPM.

1. Install the package

npm install @gojasper/mcp-server

2. Configure in your client

Add the server configuration to your AI Clients configuration file. 

// Add the following to your claude_desktop_config.json file. 

{
  "mcpServers": {
    "jasper": {
      "command": "npx",
      "args": ["-y", "@gojasper/jasper-mcp-server"],
      "env": {
        "JASPER_API_KEY": "<your-jasper-api-key>"
      }
    }
  }
}

// Add the following to your ~/.cursor/mcp.json file

{
  "mcpServers": {
    "jasper": {
      "command": "npx",
      "args": ["-y", "@gojasper/jasper-mcp-server"],
      "env": {
        "JASPER_API_KEY": "<your-jasper-api-key>"
      }
    }
  }
}


// Add the following to your .vscode/mcp.json file in your workspace

{
  "servers": {
    "jasper": {
      "command": "npx",
      "args": ["-y", "@gojasper/jasper-mcp-server"],
      "env": {
         "JASPER_API_KEY": "<your-jasper-api-key>"
      }
    }
  }
}

// Add the following to your ~/.codeium/windsurf/mcp_config.json file 

{
  "mcpServers": {
    "jasper": {
      "command": "npx",
      "args": ["-y", "@gojasper/jasper-mcp-server"],
      "env": {
         "JASPER_API_KEY": "<your-jasper-api-key>"
      }
    }
  }
}

To learn more, see the Jasper NPMJS package.

Remote Setup

Jasper hosts a streamable HTTP MCP server available at https://mcp.jasper.ai to enable easy integration with AI platforms that support remote MCP server connectors using API key authorization.

Example: Using with OpenAI Responses API

from openai import OpenAI

client = OpenAI()

resp = client.responses.create(
    model="gpt-4.1",
    input="Create a tweet promoting Duolingo for students using my social media voice and a relevant target audience",
    tools=[
        {
            "type": "mcp",
            "server_label": "jasper",
            "server_url": "https://mcp.jasper.ai",
            "headers": {
                "Authorization": "Bearer $JASPER_API_KEY"
            }
        }
    ]
)

print(resp.output_text)

import OpenAI from "openai";
const client = new OpenAI();

const resp = await client.responses.create({
    model: "gpt-4.1",
    input: "Create a tweet promoting Duolingo for students using my social media voice and a relevant target audience",
    tools: [
        {
            type: "mcp",
            server_label: "jasper",
            server_url: "https://mcp.jasper.ai",
            headers: {
                Authorization: "Bearer $JASPER_API_KEY"
            }
        }
    ]
});

console.log(resp.output_text);

curl https://api.openai.com/v1/responses \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $OPENAI_API_KEY" \
  -d '{
  "model": "gpt-4.1",
  "input": "Create a tweet promoting Duolingo for students using my social media voice and a relevant target audience",
  "tools": [
    {
      "type": "mcp",
      "server_label": "jasper",
      "server_url": "https://mcp.jasper.ai",
      "headers": {
        "Authorization": "Bearer $JASPER_API_KEY"
      }
    }
  ]
}'

To learn more, see the OpenAI documentation.

Example: Using with Anthropic's Messages API

response = anthropic.beta.messages.create(
    model="claude-sonnet-4-20250514",
    max_tokens=1000,
    messages=[{
        "role": "user",
        "content": "Using information from my knowledge base, please outline the key benefits of the Jasper MCP."
    }],
    mcp_servers=[{
      "type": "url",
      "url": "https://mcp.jasper.ai",
      "name": "jasper",
      "authorization_token": "$JASPER_API_KEY"
    }],
    betas=["mcp-client-2025-04-04"]
)

const response = await anthropic.beta.messages.create({
  model: "claude-sonnet-4-20250514",
  max_tokens: 1000,
  messages: [
    {
      role: "user",
      content: "Using information from my knowledge base, please outline the key benefits of the Jasper MCP.",
    },
  ],
  mcp_servers: [
    {
      type: "url",
      url: "https://mcp.jasper.ai",
      name: "jasper",
      authorization_token: "$JASPER_API_KEY",
    },
  ],
  betas: ["mcp-client-2025-04-04"],
});

curl https://api.anthropic.com/v1/messages \
  -H "Content-Type: application/json" \
  -H "X-API-Key: $ANTHROPIC_API_KEY" \
  -H "anthropic-version: 2023-06-01" \
  -H "anthropic-beta: mcp-client-2025-04-04" \
  -d '{
    "model": "claude-sonnet-4-20250514",
    "messages": [{"role": "user", "content": "Using information from my knowledge base, please outline the key benefits of the Jasper MCP."}],
    "mcp_servers": [
      {
        "type": "url",
        "url": "https://mcp.jasper.ai",
        "name": "jasper",
        "authorization_token": "$JASPER_API_KEY"
      }
    ]
  }'

To learn more, see the Anthropic documentation.

Updated about 9 hours ago