QuickChart MCP Server
Generates various types of charts (bar, line, pie, doughnut, radar, scatter, bubble, etc.) using Chart.js configuration format through QuickChart.io's URL-based chart generation service
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@QuickChart MCP Servercreate a bar chart showing monthly sales data for Q1"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
quickchart-server MCP Server
A Model Context Protocol server for generating charts using QuickChart.io
This is a TypeScript-based MCP server that provides chart generation capabilities. It allows you to create various types of charts through MCP tools.
Overview
This server integrates with QuickChart.io's URL-based chart generation service to create chart images using Chart.js configurations. Users can generate various types of charts by providing data and styling parameters, which the server converts into chart URLs or downloadable images.
Features
Tools
generate_chart- Generate a chart URL using QuickChart.ioSupports multiple chart types: bar, line, pie, doughnut, radar, polarArea, scatter, bubble, radialGauge, speedometer
Customizable with labels, datasets, colors, and additional options
Returns a URL to the generated chart
download_chart- Download a chart image to a local fileTakes chart configuration and output path as parameters
Saves the chart image to the specified location
Supported Chart Types
Bar charts: For comparing values across categories
Line charts: For showing trends over time
Pie charts: For displaying proportional data
Doughnut charts: Similar to pie charts with a hollow center
Radar charts: For showing multivariate data
Polar Area charts: For displaying proportional data with fixed-angle segments
Scatter plots: For showing data point distributions
Bubble charts: For three-dimensional data visualization
Radial Gauge: For displaying single values within a range
Speedometer: For speedometer-style value display
Usage
Chart Configuration
The server uses Chart.js configuration format. Here's a basic example:
{
"type": "bar",
"data": {
"labels": ["January", "February", "March"],
"datasets": [{
"label": "Sales",
"data": [65, 59, 80],
"backgroundColor": "rgb(75, 192, 192)"
}]
},
"options": {
"title": {
"display": true,
"text": "Monthly Sales"
}
}
}URL Generation
The server converts your configuration into a QuickChart URL:
https://quickchart.io/chart?c={...encoded configuration...}Development
Install dependencies:
npm installBuild the server:
npm run buildInstallation
Installing
npm install @gongrzhe/quickchart-mcp-serverInstalling via Smithery
To install QuickChart Server for Claude Desktop automatically via Smithery:
npx -y @smithery/cli install @gongrzhe/quickchart-mcp-server --client claudeTo use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"quickchart-server": {
"command": "node",
"args": ["/path/to/quickchart-server/build/index.js"]
}
}
}or
{
"mcpServers": {
"quickchart-server": {
"command": "npx",
"args": [
"-y",
"@gongrzhe/quickchart-mcp-server"
]
}
}
}Documentation References
📜 License
This project is licensed under the MIT License.
Available Tools
2 toolsdownload_chartC
Download a chart image to a local file
| Name | Required | Description | Default |
|---|---|---|---|
| config | Yes | Chart configuration object | |
| outputPath | No | Path where the chart image should be saved. If not provided, the chart will be saved to Desktop or home directory. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but provides minimal behavioral information. It mentions saving to Desktop/home directory as a fallback, which is useful, but doesn't disclose important traits like file format, permissions needed, whether it overwrites existing files, error conditions, or what happens if the config is invalid.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise - a single sentence that communicates the core functionality without any wasted words. It's front-loaded with the essential information and doesn't include unnecessary elaboration.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with no annotations, no output schema, and a nested object parameter (config), the description is insufficient. It doesn't explain what the chart configuration should contain, what image formats are supported, what happens on success/failure, or provide any context about the relationship with the sibling 'generate_chart' tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With 100% schema description coverage, the baseline is 3. The description doesn't add any parameter information beyond what's already in the schema - it doesn't explain what a 'chart configuration object' should contain, provide examples, or clarify the outputPath behavior beyond what the schema already states.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Download') and the resource ('a chart image to a local file'), making the purpose immediately understandable. However, it doesn't distinguish this tool from its sibling 'generate_chart' - it's unclear if 'download_chart' generates and downloads or just downloads an existing chart.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided about when to use this tool versus alternatives. The description doesn't mention the sibling tool 'generate_chart' or explain the relationship between generating and downloading charts, leaving the agent to guess about appropriate usage contexts.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_chartC
Generate a chart using QuickChart
| Name | Required | Description | Default |
|---|---|---|---|
| datasets | Yes | ||
| labels | No | Labels for data points | |
| options | No | ||
| title | No | ||
| type | Yes | Chart type (bar, line, pie, doughnut, radar, polarArea, scatter, bubble, radialGauge, speedometer) |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but provides minimal information. It mentions 'using QuickChart' which hints at an external service dependency, but doesn't describe what the tool actually returns (e.g., URL, image data, error handling), rate limits, authentication needs, or whether it's a read-only or mutating operation. For a tool with complex parameters and no annotations, this is inadequate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is extremely concise at just 4 words, with zero wasted language. It's front-loaded with the core functionality and uses minimal space to convey the basic purpose. Every word earns its place in this brief description.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a tool with 5 parameters (including complex nested objects), no annotations, no output schema, and a sibling tool, the description is severely incomplete. It doesn't explain what the tool returns, how to interpret results, error conditions, or how it differs from the sibling 'download_chart' tool. The minimal description leaves too many gaps for effective agent usage.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With only 40% schema description coverage, the description doesn't compensate by explaining any of the 5 parameters. The schema provides some parameter descriptions (like 'labels for data points' and 'chart type'), but the description adds no additional semantic context about what parameters mean, how they interact, or what values are expected beyond what's in the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('generate') and resource ('chart using QuickChart'), making the purpose immediately understandable. However, it doesn't differentiate from the sibling 'download_chart' tool, which appears to be a related but distinct operation. The description is specific about what the tool does but lacks sibling differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides no guidance on when to use this tool versus the sibling 'download_chart' tool, nor does it mention any prerequisites, constraints, or alternative approaches. There's no indication of when this tool is appropriate versus other chart generation methods or the sibling tool.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections. Dates show when Glama detected each change.
2 tool updates
v1.0.0- First observed
download_chart - First observed
generate_chart
TDQS
The two tools have clearly distinct purposes: generate_chart creates a chart, while download_chart saves it to a file. There is no overlap or ambiguity between these operations.
Both tools follow a consistent verb_noun pattern (generate_chart, download_chart) with clear, descriptive names that align well with their functions.
With only 2 tools, the server feels thin for a chart generation domain. While it covers basic creation and downloading, typical charting needs might include configuration, formatting, or data manipulation tools that are missing here.
The toolset is severely incomplete for chart generation. It lacks essential operations like configuring chart types, setting data, adjusting styles, or managing templates, which are core to the domain and would cause agent failures in complex tasks.
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