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Scrapi MCP Server

by bamchi
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TypeScript
Hybrid

⚡ Fast & Reliable — Built on 8+ years of web scraping expertise, 1,900+ production crawlers, and battle-tested anti-bot handling.

What is this?

An MCP (Model Context Protocol) server that lets AI agents fetch and read web pages. Simply give it a URL, and it returns clean, LLM-ready content — fast.

Before: AI can't read web pages directly
After: "Summarize this article" just works ✨

Related MCP server: url-content-mcp

Features

  • 🌐 URL → Markdown: Preserves headings, lists, links

  • 📄 URL → Text: Plain text extraction

  • 🏷️ Metadata: Title, author, date, images

  • 🧹 Clean Output: No ads, no navigation, no scripts

  • ⚡ JavaScript Rendering: Works with SPAs

  • 💳 Built-in Billing: Credit tracking, subscription management, usage analytics (MCP keys)

  • 🔄 Auto-Retry: 429 rate limit responses automatically retried with Retry-After

  • 🌍 Dual Transport: Stdio (npx) + Streamable HTTP for flexible deployment

Transport Modes

Scrapi MCP Server supports two transport modes:

Mode

Best For

Node.js Required

Stdio

Claude Desktop, Cursor, Cline, Claude Code

Yes (auto via npx)

Streamable HTTP

All clients, Node.js-free environments

No

Prerequisites

  • Scrapi MCP account (separate from the main Scrapi account)

  • Claude Desktop, Cline, or Cursor installed

  • Node.js 20+

Installation

Option A: npx (Recommended)

No installation needed. Just configure your MCP client to use npx.

{
  "mcpServers": {
    "scrapi": {
      "command": "npx",
      "args": ["-y", "@scrapi.ai/mcp-server"],
      "env": {
        "SCRAPI_API_KEY": "your-api-key"
      }
    }
  }
}

Tip: You can also pass the API key via CLI argument instead of env var:

"args": ["-y", "@scrapi.ai/mcp-server", "--api-key", "your-api-key"]

See Step 2 for where to put this configuration.

Option B: Install from Source

# Clone the repository
git clone https://github.com/bamchi/scrapi-mcp-server.git
cd scrapi-mcp-server

# Install dependencies and build
npm install && npm run build

Step 1: Get Your API Key

  1. Go to https://scrapi.ai

  2. Sign up or log in

  3. Visit the MCP Dashboard — your Free plan (500 credits/month) and API key are created automatically

  4. Copy your hsmcp_ API key

Step 2: Configure MCP Server

Claude Desktop

Option A: Via Settings (Recommended)

  1. Open Claude Desktop

  2. Click Settings (gear icon, bottom left)

  3. Select Developer tab

  4. Click "Edit Config" button

  5. Add the mcpServers configuration (see below)

  6. Save and restart Claude Desktop (Cmd+Q, then reopen)

Option B: Edit config file directly

  • macOS: ~/Library/Application Support/Claude/claude_desktop_config.json

  • Windows: %APPDATA%\Claude\claude_desktop_config.json

Configuration (npx):

{
  "mcpServers": {
    "scrapi": {
      "command": "npx",
      "args": ["-y", "@scrapi.ai/mcp-server"],
      "env": {
        "SCRAPI_API_KEY": "your-api-key"
      }
    }
  }
}

Configuration (from source):

{
  "mcpServers": {
    "scrapi": {
      "command": "node",
      "args": ["/absolute/path/to/scrapi-mcp-server/dist/index.js"],
      "env": {
        "SCRAPI_API_KEY": "your-api-key"
      }
    }
  }
}

Note: Replace /absolute/path/to/ with the actual path where you cloned the repository.

Cline

Config file location:

  • macOS: ~/Library/Application Support/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json

  • Windows: %APPDATA%\Code\User\globalStorage\saoudrizwan.claude-dev\settings\cline_mcp_settings.json

Configuration (npx):

{
  "mcpServers": {
    "scrapi": {
      "command": "npx",
      "args": ["-y", "@scrapi.ai/mcp-server"],
      "env": {
        "SCRAPI_API_KEY": "your-api-key"
      }
    }
  }
}

Configuration (from source):

{
  "mcpServers": {
    "scrapi": {
      "command": "node",
      "args": ["/absolute/path/to/scrapi-mcp-server/dist/index.js"],
      "env": {
        "SCRAPI_API_KEY": "your-api-key"
      }
    }
  }
}

Cursor

Create or edit .cursor/mcp.json in your project root:

Configuration (npx):

{
  "mcpServers": {
    "scrapi": {
      "command": "npx",
      "args": ["-y", "@scrapi.ai/mcp-server"],
      "env": {
        "SCRAPI_API_KEY": "your-api-key"
      }
    }
  }
}

Configuration (from source):

{
  "mcpServers": {
    "scrapi": {
      "command": "node",
      "args": ["/absolute/path/to/scrapi-mcp-server/dist/index.js"],
      "env": {
        "SCRAPI_API_KEY": "your-api-key"
      }
    }
  }
}

Claude Code

Option 1: CLI command (Recommended)

claude mcp add scrapi-ai -s user -e SCRAPI_API_KEY=your-api-key -- npx -y @scrapi.ai/mcp-server

Or with --api-key:

claude mcp add scrapi-ai -s user -- npx -y @scrapi.ai/mcp-server --api-key your-api-key

Option 2: Edit config file

Edit ~/.claude.json or project .mcp.json:

{
  "mcpServers": {
    "scrapi": {
      "command": "npx",
      "args": ["-y", "@scrapi.ai/mcp-server", "--api-key", "your-api-key"]
    }
  }
}

Streamable HTTP

Connect via Streamable HTTP — no Node.js installation needed on the client side.

Endpoint: https://scrapi.ai/mcp

Cursor (.cursor/mcp.json):

{
  "mcpServers": {
    "scrapi": {
      "url": "https://scrapi.ai/mcp",
      "headers": {
        "Authorization": "Bearer your-api-key"
      }
    }
  }
}

Claude Code (CLI):

claude mcp add --transport http scrapi https://scrapi.ai/mcp \
  --header "Authorization: Bearer your-api-key"

Cline (cline_mcp_settings.json):

{
  "mcpServers": {
    "scrapi": {
      "type": "streamableHttp",
      "url": "https://scrapi.ai/mcp",
      "headers": {
        "Authorization": "Bearer your-api-key"
      }
    }
  }
}

Claude Desktop (claude_desktop_config.json):

{
  "mcpServers": {
    "scrapi": {
      "command": "npx",
      "args": [
        "mcp-remote",
        "https://scrapi.ai/mcp",
        "--header",
        "Authorization: Bearer your-api-key"
      ]
    }
  }
}

Note: Claude Desktop requires the mcp-remote proxy for HTTP connections.

Run your own instance instead of using the hosted endpoint:

SCRAPI_API_KEY=your-api-key npx -y -p @scrapi.ai/mcp-server scrapi-http
# or from source:
SCRAPI_API_KEY=your-api-key node dist/http.js

The server starts at http://localhost:3000 with the MCP endpoint at /mcp. Configure with PORT and HOST environment variables. Replace the URL in the client configurations above with your self-hosted URL (e.g. http://localhost:3000/mcp).

Health check: GET http://localhost:3000/health

Step 3: Restart Your AI Client

  • Claude Desktop: Fully quit (Cmd+Q on macOS, Alt+F4 on Windows) and reopen

  • Claude Code: Restart the session

  • Cline: Restart VS Code

  • Cursor: Restart the editor

You should see the MCP server connection indicator.

Available Tools

scrape_url

Scrapes a webpage and returns AI-readable content.

Parameters:

Name

Type

Required

Description

url

string

✅

URL to scrape

format

string

markdown (default) or text

Example:

{
  "url": "https://example.com/article",
  "format": "markdown"
}

Markdown Output:

# Article Title

> Author: John Doe | Published: 2024-01-15

## Introduction

This is the main content of the article, converted to clean markdown...

## Key Points

- Point 1: Important detail
- Point 2: Another insight
- [Related Link](https://example.com/related)

Text Output:

Article Title

Author: John Doe | Published: 2024-01-15

Introduction

This is the main content of the article, converted to plain text...

Key Points

- Point 1: Important detail
- Point 2: Another insight

scrape_urls

Scrapes multiple webpages in parallel and returns AI-readable content.

Parameters:

Name

Type

Required

Description

urls

string[]

✅

URLs to scrape (max 10)

format

string

markdown (default) or text

Example:

{
  "urls": ["https://example.com/page1", "https://example.com/page2"],
  "format": "text"
}

Output:

[
  {
    "url": "https://example.com/page1",
    "content": "Page 1 Title\n\nThis is the content of page 1..."
  },
  {
    "url": "https://example.com/page2",
    "content": "Page 2 Title\n\nThis is the content of page 2..."
  }
]

scraper_server_status

Check the status of all ScraperServer instances. Shows server health, circuit breaker state, failure counts, and timing info.

Parameters: None

Example:

{}

Output:

## ScraperServer Status

Total: 3 | Available: 2

| Name | OS | Status | Failures | Last Success | Last Failure |
|------|----|--------|----------|--------------|--------------|
| pluto | linux | OK | 0 | 01/30 14:23:05 | - |
| mars | mac | FAIL | 2 | 01/29 10:00:00 | 01/30 13:55:12 |
| venus | linux | OPEN | 3 | 01/28 09:00:00 | 01/30 12:00:00 |

### Issues
- **mars**: Connection refused - connect(2)
- **venus**: Circuit breaker open until 01/30 12:30:00
- **venus**: Net::ReadTimeout

Status values:

Status

Description

OK

Server is healthy

FAIL

Server is unhealthy

OPEN

Circuit breaker open (isolated for 30 min)

N/A

Not yet checked

get_usage

Check your API usage and remaining credits.

Parameters: None

Example:

{}

Output:

## MCP Credits

| Item | Value |
|------|-------|
| Plan | starter |
| Subscription Credits | 1,500 |
| Purchased Credits | 200 |
| Total Remaining | 1,700 |
| Period End | 2026-03-01 |

get_billing

Retrieve detailed billing information including subscription, plans, daily usage, and spending limits.

Parameters:

Name

Type

Required

Description

action

string

Yes

subscription, plans, daily_usage, or spending_limits

start_date

string

Start date for daily_usage (YYYY-MM-DD, default: 30 days ago)

end_date

string

End date for daily_usage (YYYY-MM-DD, default: today)

Example — Current subscription:

{ "action": "subscription" }
## MCP Subscription

| Item | Value |
|------|-------|
| Plan | starter (Starter) |
| Status | active |
| Monthly Credits | 2,000 |
| Price | $19.00/mo |
| Rate Limit | 30 RPM |
| Burst Limit | 5 concurrent |
| Period End | 2026-03-01 |

Example — Available plans:

{ "action": "plans" }
## Available MCP Plans

| Plan | Credits/mo | Price | RPM | Burst |
|------|-----------|-------|-----|-------|
| Free (free) | 500 | Free | 10 | 2 |
| Starter (starter) | 2,000 | $19.00/mo | 30 | 5 |
| Pro (pro) | 10,000 | $49.00/mo | 60 | 10 |
| Business (business) | 50,000 | $149.00/mo | 120 | 20 |

Example — Daily usage history:

{ "action": "daily_usage", "start_date": "2026-02-01", "end_date": "2026-02-07" }
## Daily Usage (2026-02-01 ~ 2026-02-07)

| Date | Requests | Credits | Top Tool |
|------|----------|---------|----------|
| 2026-02-07 | 45 | 45 | scrape#scrape (45) |
| 2026-02-06 | 120 | 120 | scrape#scrape (100) |

**Total**: 165 requests, 165 credits

Example — Spending limits:

{ "action": "spending_limits" }
## Spending Limits

| Item | Value |
|------|-------|
| Daily Limit | 500 credits |
| Today's Usage | 120 credits |
| Usage % | 24.0% |

Usage Examples

Example 1: Summarize a News Article

User: Summarize this article: https://news.example.com/article/12345

Claude: [calls scrape_url]

Here's a summary of the article:

## Key Points
- Point 1: ...
- Point 2: ...
- Point 3: ...

Example 2: Fetch Page Content

User: Get the content from https://example.com/data

Claude: [calls scrape_url]

# Page Title
> Source: https://example.com/data

The page content is returned in clean Markdown format...

Example 3: Research Competitor Pricing

User: What's the pricing on https://competitor.com/product/abc

Claude: [calls scrape_url]

Here's the pricing information:
- **Product**: ABC Premium
- **Regular Price**: $99.00
- **Sale Price**: $79.00 (20% off)

Example 4: Read API Documentation

User: Read https://docs.example.com/api/v2 and write integration code

Claude: [calls scrape_url]

I've analyzed the API documentation. Here's the integration code:

// api-client.ts
export class ExampleApiClient {
  private baseUrl = 'https://api.example.com/v2';
  
  async getData(): Promise<Response> {
    // ...
  }
}

How It Works

┌─────────────────┐
│     User        │
│ "Summarize this │
│   URL for me"   │
└────────┬────────┘
         │
         ▼
┌─────────────────┐
│  Claude Desktop │
│    / Cursor     │
└────────┬────────┘
         │
         ▼
┌─────────────────┐     ┌─────────────────┐
│   MCP Server    │────►│   Scrapi API    │
│  (scrape_url)   │     │ (format param)  │
└────────┬────────┘     └────────┬────────┘
         │                       │
         │◄──────────────────────┘
         │   Markdown/Text Response
         ▼
┌─────────────────┐
│   AI Response   │
│ (Summary, etc.) │
└─────────────────┘

Why Scrapi?

Built by the team behind Scrapi, with 8+ years of web scraping experience:

  • ✅ 1,900+ production crawlers

  • ✅ JavaScript rendering support

  • ✅ Anti-bot handling

  • ✅ 99.9% uptime

Troubleshooting

"API key is required"

Make sure your API key is provided via one of these methods:

  • Environment variable: Set SCRAPI_API_KEY in your configuration

  • CLI argument: Pass --api-key your-key in the args

"Invalid API key"

Verify that your API key is correct and active in your Scrapi dashboard.

npx using an old cached version

If you upgraded but still see old behavior, clear the npx cache:

npx clear-npx-cache

MCP Server not connecting

  1. Ensure Node.js 20+ is installed

  2. Try running node /absolute/path/to/scrapi-mcp-server/dist/index.js manually to check for errors

  3. Fully quit Claude Desktop (Cmd+Q on macOS, Alt+F4 on Windows) and restart

  4. Check Settings > Developer to verify the server is listed

Developer tab not visible

Update Claude Desktop to the latest version: Claude menu → "Check for Updates..."

Support

License

MIT © Scrapi

Available Tools

5 tools
get_billingBInspect

Retrieve MCP billing information: subscription details, available plans, daily usage history, or spending limits.

ParametersJSON Schema
NameRequiredDescriptionDefault
actionYesWhat billing info to retrieve: subscription (current plan details), plans (available plans), daily_usage (credit usage history), spending_limits (daily spend limit status)
start_dateNoStart date for daily_usage (YYYY-MM-DD). Default: 30 days ago
end_dateNoEnd date for daily_usage (YYYY-MM-DD). Default: today

TDQS

B3.3/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must fully disclose behavior. It states 'Retrieve' but lacks details on side effects, return format, error handling, or permissions. The default date info is helpful but insufficient.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Single sentence is concise and covers main purpose, though listing subcategories could be slightly more structured. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no output schema and multiple action types, description should hint at return values for each action. It only echoes schema's action list without clarifying what each returns or how date params interact with non-usage actions.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100% with clear enum for action. Description adds default values for start_date and end_date (30 days ago and today), which the schema lacks, enhancing parameter semantics.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description clearly states 'Retrieve MCP billing information' and enumerates specific subcategories (subscription, plans, daily_usage, spending_limits), distinguishing from sibling tools like get_usage and scraper_server_status.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No explicit guidance on when to use this tool vs alternatives. While context suggests billing focus, no when/when-not conditions or mentions of sibling tools are provided.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

get_usageAInspect

Check API usage and remaining credits. Returns current plan, subscription credits, purchased credits, and total remaining credits.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A3.7/5.0
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations provided, so description must disclose behaviors. It only states it checks usage, but no side-effects, authentication, or safety info. It is a read operation but not explicitly stated.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two sentences front-load purpose and list returns. No unnecessary words or redundancy.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple parameterless read tool, the description explains all returned values. No output schema needed given clarity.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

No parameters exist, so description adds meaning by explaining return fields. It compensates for the lack of output schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks API usage and remaining credits, listing specific return values. It distinguishes from sibling tools like get_billing (billing info) and scrape_urls (scraping).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like get_billing. The description simply states what it does without usage context.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

scraper_server_statusAInspect

Check the status of all ScraperServer instances. Shows server health, circuit breaker state, failure counts, and last success/failure times.

ParametersJSON Schema
NameRequiredDescriptionDefault

No parameters

TDQS

A4.5/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description indicates a read-only operation ('Check', 'Shows') without explicit read-only flag, but no annotations exist. It does not mention any destructive side effects or required permissions, which is acceptable for a simple status check. The listed outputs provide adequate behavioral context.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is only two sentences (about 20 words), directly stating the purpose and what is shown. No unnecessary words or repetition. It front-loads the key action and then provides specifics.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given no parameters and no output schema, the description fully explains the tool's role and outputs. It covers server health, circuit breaker, failure counts, and times, which is complete for a status check tool.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The tool has no parameters, and the schema coverage is 100% (no undocumented parameters). The description does not add parameter-level detail because none are needed. Baseline score 4 for zero parameters.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool checks the status of all ScraperServer instances, listing specific metrics (server health, circuit breaker state, failure counts, times). It is easily distinguished from siblings which deal with billing, usage, or scraping URLs.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage for monitoring system health, with clear context. No explicit when-not-to-use or alternatives are provided, but the context is sufficient for an agent to infer when to use this tool.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

scrape_urlAInspect

Scrapes a webpage and returns the content in AI-readable Markdown format. Can access blocked sites through browser rendering.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlYesThe URL of the webpage to scrape
formatNoOutput format: markdown (default) or textmarkdown

TDQS

A3.6/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Discloses ability to access blocked sites via browser rendering. Without annotations, this provides valuable behavioral context. However, lacks details on rate limits or output size.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Two concise sentences with key information front-loaded. No wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Sufficient for a simple two-parameter tool with no output schema. Covers core functionality and a notable feature (blocked sites). Could mention error handling but not essential.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema already describes both parameters fully. Description adds no extra meaning beyond what's in schema, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Clearly states it scrapes a webpage and returns markdown. Distinguishes from siblings via mention of accessing blocked sites, but does not explicitly differentiate from scrape_urls.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives like scrape_urls. Does not specify prerequisites or when not to use.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

scrape_urlsAInspect

Scrapes multiple webpages in parallel and returns the content in AI-readable Markdown format. Can access blocked sites through browser rendering.

ParametersJSON Schema
NameRequiredDescriptionDefault
urlsYesURLs to scrape (max 10)
formatNoOutput format: markdown (default) or textmarkdown

TDQS

A3.8/5.0
Behavior3/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Without annotations, the description discloses key behaviors: parallel scraping and browser rendering to access blocked sites. However, it omits potential limitations like rate limits, authentication requirements, or cost implications.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise with two sentences, no wasted words. The key purpose is front-loaded, and every sentence adds value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the moderate complexity (parallel, multiple URLs, output format options) and absence of an output schema, the description covers the main purpose and distinctive feature (browser rendering). However, it does not mention the 'text' format option or handle edge cases like errors or limits, but the schema provides format details.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema already covers both parameters (urls and format) with descriptions. The description does not add new detail about parameter usage or constraints, but provides context about the overall process. Given 100% schema coverage, a score of 3 is appropriate.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the action (scrapes), resource (multiple webpages), and distinctive features (parallel, browser rendering for blocked sites). It differentiates from sibling tool 'scrape_url' by emphasizing parallelism.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies when to use (e.g., for blocked sites) but does not explicitly state when not to use, such as for single URLs, nor does it mention alternatives like 'scrape_url' or other tools.

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. 5 tool updatesv3.2.0
    • First observedget_billing
    • First observedget_usage
    • First observedscrape_url
    • First observedscrape_urls
    • First observedscraper_server_status
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TDQS

A3.7/5.0
Disambiguation4/5

Each tool has a distinct purpose: billing info, usage credits, server status, single scrape, and batch scrape. The two billing/usage tools are related but their descriptions clearly differentiate scope, so an agent can distinguish them.

Naming Consistency3/5

Most tools follow verb_noun pattern (e.g., get_billing, scrape_url), but 'scraper_server_status' uses a noun phrase without a clear verb, introducing inconsistency. The naming is readable but not fully uniform.

Tool Count5/5

With 5 tools, the set is well-scoped for the server's purpose: core scraping functionality (single and batch), server monitoring, and account/usage management. Each tool is necessary and none are redundant.

Completeness3/5

The tool set covers essential actions like scraping and checking status/billing, but lacks management operations such as stopping a scrape, updating billing plans, or configuring scrape options. This creates notable gaps that agents may need to work around.

Maintenance

ActivityInactive
ResponsivenessSyncing

Resources

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