Browser Use
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Description from the maker (original English)
The open chart format an LLM writes and the browser renders — to interactive, accessible SVG.
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We have not written a plain-language summary for this one yet. Below are the facts we read from the registry.
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Open Claude Desktop → Settings → Developer → Edit Config, and paste this into claude_desktop_config.json
{
"mcpServers": {
"blueprint-chart": {
"command": "npx",
"args": [
"-y",
"@blueprint-chart/mcp"
]
}
}
}Run this in your terminal
claude mcp add blueprint-chart -- npx -y @blueprint-chart/mcpPaste into .cursor/mcp.json in your project, or ~/.cursor/mcp.json
{
"mcpServers": {
"blueprint-chart": {
"command": "npx",
"args": [
"-y",
"@blueprint-chart/mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
Paste into .vscode/mcp.json in your project
{
"servers": {
"blueprint-chart": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@blueprint-chart/mcp"
]
}
}
}Your browser asks to open the app, then the app shows the settings and asks you to confirm. Key values are left empty for you to fill in.
This one runs on your computer, and ChatGPT can only connect to servers on the internet. Pick another app.
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These settings are generated from the maker’s registry entry. If the README says otherwise, follow the README.
Runs on your computer; the tool list appears in your AI app after you install it.
We check information anyone can see; we have not read the code. Checks that do not apply are left out of the count. · Checked Nov 7, 2026
The registry name was verified with the GitHub account blueprint-chart, which owns the repo
We have not read this repo from GitHub yet
We have not read this repo from GitHub yet
This one runs on your computer; there is no internet endpoint
Runs on your computer and uses local settings instead
Runs on your computer; we can only read tool lists from internet endpoints
Compared with every active server in this category in the registry. Stars count only when the publisher owns the repo.
It passed 1 of 1 applicable basic checks. We have not read the code. Before adding a key or token, see what access the server asks for and use a key with only the permissions you need.
The registry does not list a required key, though some servers ask you to sign in on first use.
It runs on your computer. Your AI app starts it when needed, and data does not pass through the maker’s servers (unless it calls an online service itself).
The GitHub repo last changed –, and the latest version (0.2.1) reached the registry 2 months ago.
Apps that support MCP, such as Claude Desktop, Claude Code, Cursor and VS Code. You also need Node.js on your computer.
In the same category: Browser Use, Chrome DevTools MCP, MCP Server Browser
Servers in the same category from other makers, sorted by stars.
Reading a card:★ GitHub starsiThree pillars: reviews · checks · usageiUpdated = latest version published to the registryi
Lets AI do web tasks for you, such as filling forms, searching and extracting data, in the maker’s cloud browsers or on your computer.
Lets AI use Chrome’s developer tools to inspect pages, find what makes them slow and spot errors. Made by the Chrome DevTools team.
MCP server for browser use access
Copied from the maker’s repo as written. PopNx MCP has not reviewed or endorsed it. HTML, images and scripts are removed. Links lead off this site.
Model Context Protocol server for authoring Blueprint Chart .bpc files with LLMs, grounded in real dataviz pedagogy with a tight parse + render feedback loop. An open, plain-text chart format an AI can write and any browser can render. Self-contained, no backend, no account required.
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The MCP exposes Blueprint Chart's dataviz handbook, DSL grammar reference, chart-type docs, and canonical samples as MCP resources, plus eleven deterministic tools: validate_dsl, inspect_dsl, recommend_chart_type, render, list_chart_types, describe_chart_type, get_example, get_grammar, export_chart, search_examples, and list_palettes. Your LLM writes the .bpc; the MCP grounds it in real dataviz pedagogy and gives it a tight feedback loop.
npx @blueprint-chart/mcp # stdio (for Claude Desktop, Claude Code, Cursor)
npx @blueprint-chart/mcp --http # HTTP/SSE on 127.0.0.1:4321
Add to claude_desktop_config.json:
{
"mcpServers": { "blueprint-chart": { "command": "npx", "args": ["-y", "@blueprint-chart/mcp"] } } }
claude mcp add blueprint-chart \
-e BLUEPRINT_CHART_EDITOR_URL=https://blueprintchart.com \ -e BLUEPRINT_CHART_DOCS_URL=https://docs.blueprintchart.com \ -- npx -y @blueprint-chart/mcp
| Tool | Purpose |
|---|---|
validate_dsl | Parse .bpc; returns { valid, errors[], warnings[] } — each error has code, message, suggestion |
inspect_dsl | Parse and summarize: chartType, scenes, seriesCount, rowCount, hasHighlights, hasColorizes, etc. |
recommend_chart_type | Rank chart types for a given column shape and row count |
render | Render to SVG (default), PNG, or HTML; with format:"png" returns an inline image both you and the user can see. Always returns structured frame metadata. When MCP_PUBLIC_URL is set, includes urls ({png,svg,bpc}) — stateless links where the chart data travels inside the URL. Set modelVisible:false to drop the inline image from the response entirely, spending no image tokens. Pass save: to write the output to disk (requires MCP_FS_WRITE_DIR; writes are confined to that directory). Width/height capped at 1600; PNG is 2× retina. |
list_chart_types | List all renderable chart types (tool equivalent of bpc://handbook/choosing) |
describe_chart_type | Properties, when-to-use, when-NOT-to-use, and data-shape for one chart type (tool equivalent of bpc://chart-types/{slug}) |
get_example | Fetch a canonical .bpc sample by chart type or sample name (tool equivalent of bpc://samples/{id}) |
search_examples | Find canonical examples by topic keywords and/or chart type (returns pointers; fetch full DSL with get_example) |
get_grammar | Full DSL syntax reference (tool equivalent of bpc://grammar) |
list_palettes | List named colour palettes with hex colours for colorPalette |
export_chart | Validate a .bpc and return shareable URLs plus an inline preview. Returns { copyUrl, embedUrl, urls?, frame } — copyUrl is editable in the editor, embedUrl is a read-only iframe target, urls.{png,svg,bpc} are stateless rendered/source links (when MCP_PUBLIC_URL is set). Set modelVisible:false to drop the inline preview from the response entirely, spending no image tokens. Requires BLUEPRINT_CHART_EDITOR_URL; preview failures never block the export. |
The discovery tools (list_chart_types, describe_chart_type, get_example, search_examples, get_grammar, list_palettes) let clients without MCP resource support access the same reference material that the bpc:// URIs expose.
The render tool can write its output to disk via save: . This is disabled by default. Set MCP_FS_WRITE_DIR to a directory to enable it — ideally an absolute path; a relative value is resolved from the server's working directory at startup. Every write lands inside that directory (a sandbox), so you never have to worry about where a client puts files: relative save paths are joined to it, an absolute path already inside it is used as-is, and any other absolute path is re-anchored under it (the leading slash is stripped and the rest joined on, so save: "/tmp/foo.png" becomes /tmp/foo.png). Only paths that still escape via ../ traversal are rejected. Missing subdirectories are created automatically. Containment is checked lexically (no realpath), so a symlink whose lexical path is inside the sandbox still passes the check and is then resolved by the OS at write time — if its target is outside the sandbox, the write reaches it. Avoid placing symlinks in the sandbox if isolation matters to you.
Add the -e flag to your claude mcp add command:
claude mcp add blueprint-chart \
-e MCP_FS_WRITE_DIR=/path/to/output \ -- npx -y @blueprint-chart/mcp
bpc://grammar — full DSL syntax referencebpc://handbook/ — dataviz pedagogy (choosing, design-principles, color, typography, annotations, accessibility, ...)bpc://guide/ — usage guides (scenes, palettes, data-transforms, ...)bpc://chart-types/ — per-chart-type docsbpc://samples/ — canonical .bpc examplesbpc://reference/dsl/ , bpc://reference/api/ — full referenceauthor_chart — primes the LLM end-to-end (read → write → validate → render → iterate)Once the MCP is connected, ask Claude to make a chart:
You: Make a horizontal bar chart of English letter frequencies — top 10, highlight E.
Claude: *(calls
list_chart_types,get_example({ chartType: "bar-horizontal" }), writes the.bpc, callsvalidate_dslto confirm it parses, callsrenderwithformat: 'png'and shows you the image and the source)*
Here's the chart:
![image]
`
chart bar-horizontal {
title = "E is the most frequent letter in English"
sort = descending
valueLabels = true
highlight "E"
data { "E" = 12.70; "T" = 9.06; "A" = 8.17; ... }
}
`
The MCP grounds Claude in real dataviz pedagogy (the handbook) before it writes a single line of DSL, then closes the loop with deterministic parse + render feedback.
.bpc looks likechart bar-vertical {
title = "E is the most frequent letter in English" description = "How often each letter appears in typical English text" source = "Lewand, Cryptological Mathematics" colorPalette = "London" sort = descending valueLabels = true highlight "E"
data { "E" = 12.70 "T" = 9.06 "A" = 8.17 "O" = 7.51 ... } }
Full grammar at bpc://grammar; 17 canonical samples at bpc://samples/ (letter-frequency, co2-emissions, quarterly-revenue, browser-market, temperature-anomaly, population-stacked-bar, ...).
validate_dsl — parse with structured diagnosticsRequest:
{
"name": "validate_dsl", "arguments": { "source": "chart bar-vertical {\n title = \"oops\n}" } }
Response — valid is false; each entry in errors[] carries a code, human-readable message, and an actionable suggestion:
{
"valid": false, "errors": [ { "code": "E_PARSE", "message": "Expected \"\\\"\" but end of input found.", "suggestion": "Close the string literal on line 2." } ], "warnings": [] }
inspect_dsl — structured summaryRequest:
{ "name": "inspect_dsl", "arguments": { "source": "<.bpc source>" } }
Response:
{
"ok": true, "data": { "chartType": "bar-vertical", "scenes": [{ "index": 1, "hasTransition": false }], "hasAnnotations": false, "hasColorizes": false, "hasHighlights": true, "hasAreaFills": false, "seriesCount": 0, "rowCount": 26 } }
recommend_chart_type — ranked suggestionsRequest:
{
"name": "recommend_chart_type", "arguments": { "columnTypes": ["date", "number", "number", "number"], "rowCount": 24 } }
Response:
{
"ok": true, "data": { "recommendations": [ { "chartType": "line-multi", "label": "Multi-Line Chart", "fitness": "best", "reason": "1 date + 3 numeric columns — compare trends" }, { "chartType": "bar-multi", "label": "Grouped Bar Chart", "fitness": "alternative", "reason": "Can also show as grouped bars" } ] } }
render — SVG (default), PNG, or HTMLRequest:
{
"name": "render", "arguments": { "source": "<.bpc source>", "format": "png", "width": 800, "height": 500 } }
Response:
{
"ok": true, "data": { "svg": " ... ", "png": " ", "mimeType": "image/png", "urls": { "png": "https://mcp.blueprintchart.com/render.png?bpc64=…", "svg": "https://mcp.blueprintchart.com/render.svg?bpc64=…", "bpc": "https://mcp.blueprintchart.com/render.bpc?bpc64=…" } } }
The urls field is only present when MCP_PUBLIC_URL is configured; every render and export_chart response then includes these stateless links, with the chart data travelling inside the URL (as bpc64, a URL-safe base64 encoding of the .bpc source) — no session, no server state required. Set modelVisible:false in the request to drop the inline image from the response entirely, spending no image tokens.
If rasterization fails (rare), errors[] is non-empty — each entry has a code ("E_RENDER") and a suggestion — and the response still includes the SVG that was successfully produced, so partial success is preserved.
Embed a chart directly in a page:
<img src="https://<your-mcp-host>/render.png?bpc64=<bpc64value>&width=800&height=500" alt="My chart" width="800" height="500">
/render.bpc serves the raw .bpc source — it's "view source" for any chart URL, handy for sharing or reproducing a chart from its link alone.
Sources whose encoding exceeds 8 KB return 413 from the endpoints (and the tool omits urls, returning urlsOmitted: "source-too-large" instead) — use the inline PNG for very large charts.
{ "uri": "bpc://handbook/choosing" }
Returns the full Markdown of the "Choosing the Right Chart" handbook page (same content as docs.blueprintchart.com).
{ "uri": "bpc://samples/letter-fOnly the beginning is shown; read the rest in the repo