webfetch-camouflage
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., "@webfetch-camouflagefetch https://example.com with chrome impersonation"
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.
webfetch-camouflage-mcp

Webfetch Camouflage is an MCP server for fetching web content with browser camouflage using curl_cffi. It mimics real browser TLS/HTTP2 fingerprints to bypass bot detection, returning clean Markdown output converted from HTML.
Installation
Add to .cursor/mcp.json:
{
"mcpServers": {
"webfetch-camouflage": {
"command": "uvx",
"args": ["git+https://github.com/tianhuil/webfetch-camouflage-mcp.git"]
}
}
}claude mcp add-json webfetch-camouflage '{"command":"uvx","args":["git+https://github.com/tianhuil/webfetch-camouflage-mcp.git"]}'code --add-mcp '{"name":"webfetch-camouflage","command":"uvx","args":["git+https://github.com/tianhuil/webfetch-camouflage-mcp.git"]}'gemini mcp add webfetch-camouflage uvx -- git+https://github.com/tianhuil/webfetch-camouflage-mcp.gitcodex mcp add webfetch-camouflage -- uvx git+https://github.com/tianhuil/webfetch-camouflage-mcp.gitAdd to opencode.json:
macOS/Linux: ~/.local/share/opencode/opencode.json
Windows: %LOCALAPPDATA%\opencode\opencode.json
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"webfetch-camouflage": {
"type": "local",
"command": ["uvx", "git+https://github.com/tianhuil/webfetch-camouflage-mcp.git"],
"enabled": true
}
}
}Related MCP server: Fetch MCP
Tool reference
The fetch_url tool accepts:
url(required): URL to fetchimpersonate(optional, default"chrome"): browser profile to impersonatetimeout(optional, default10): request timeout in secondsmax_chars(optional): maximum characters to return; truncates with...if set
Supported impersonation profiles:
Chrome:
chrome99,chrome100,chrome101,chrome104,chrome107,chrome110,chrome116,chrome119,chrome120,chrome123,chrome124,chrome131,chrome133a,chrome136Firefox:
firefox133,firefox135Safari:
safari153,safari155,safari170,safari180,safari184,safari260Edge:
edge99,edge101,edge133,edge135
Notes on Development
Setup
git clone https://github.com/tianhuil/webfetch-camouflage-mcp.git
cd webfetch-camouflage-mcp
uv syncRunning the server
uv run webfetch-camouflage-mcpAvailable tasks
poe test # Run tests
poe lint # Lint code
poe format # Format code
poe typecheck # Type check
uv run pip-audit # Security auditMCP server testing
Test the server directly via JSON-RPC:
echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "test", "version": "1.0"}}}' | uv run webfetch-camouflage-mcp
echo '{"jsonrpc": "2.0", "id": 1, "method": "initialize", "params": {"protocolVersion": "2024-11-05", "capabilities": {}, "clientInfo": {"name": "test", "version": "1.0"}}}' | uvx git+https://github.com/tianhuil/webfetch-camouflage-mcp.gitOr use the helper script:
uv run python src/get_tool_details.pyAvailable Tools
1 toolfetch_urlA
Fetch web content from a URL with browser camouflage.
Args: url: The URL to fetch impersonate: Browser to impersonate (default: 'chrome'). Can be any string - curl_cffi will attempt to use the corresponding browser fingerprint. Common values include: chrome99, chrome100, chrome101, chrome104, chrome107, chrome110, chrome116, chrome119, chrome120, chrome123, chrome124, chrome131, chrome133a, chrome136, chrome99_android, chrome131_android, safari153, safari155, safari170, safari180, safari184, safari260, safari172_ios, safari180_ios, safari184_ios, safari260_ios, firefox133, firefox135, firefox135_android, tor145, edge99, edge101, edge133, edge135 timeout: Request timeout in seconds (default: 10) max_chars: Maximum number of characters to return in the response. If None, returns the full content (default: None)
Returns: The fetched content converted to Markdown format, or an error message if the request fails.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | ||
| impersonate | No | chrome | |
| timeout | No | ||
| max_chars | No |
Output Schema
| Name | Required | Description |
|---|---|---|
| result | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It explains the fetch, browser impersonation, Markdown conversion, and error conditions. However, it lacks details on potential issues like rate limiting, authentication requirements, or behavior on invalid URLs, which would improve transparency.
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 well-structured with a clear summary line followed by argument and return documentation. The list of impersonation values is lengthy but informative. It earns its place, though it could be slightly more concise.
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?
Given the tool's simplicity, the presence of an output schema (which we assume documents return structure), and the description's coverage of all parameters and behavior (including conversion to Markdown), the description is complete for an AI agent to use correctly.
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?
The input schema has no descriptions (coverage 0%), but the description provides extensive semantics for all four parameters, including default values, examples for impersonate, and explanation of max_chars behavior. This adds significant meaning beyond 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 states 'Fetch web content from a URL with browser camouflage,' which clearly defines the tool's action and resource. It also specifies a unique feature (browser camouflage), making it easily distinguishable even without sibling tools.
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?
While no explicit when-to-use or when-not-to-use guidance is given, the description thoroughly explains the tool's purpose and parameters. The absence of sibling tools reduces the need for alternatives comparison, so the description is clear enough for an AI agent to decide.
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.
1 tool update
v0.1.0- First observed
fetch_url
TDQS
Only one tool exists, so there is no risk of confusion between tools.
The single tool name 'fetch_url' follows a clear verb_noun pattern, consistent with best practices.
With one tool, the server is minimal but still reasonable for its narrow purpose of fetching URLs with browser camouflage.
The tool fully covers the advertised functionality (fetching web content with impersonation), with no obvious gaps for its stated domain.
Maintenance
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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