capskip-mcp
OfficialProvides tools to solve Cloudflare Turnstile challenges, returning a token for form submission.
Provides tools to solve Google reCAPTCHA v2/v3/Enterprise challenges, returning a token for form submission.
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., "@capskip-mcpsolve the reCAPTCHA on this page and submit the form"
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.
CapSkip MCP Server — Unlimited Captcha Solver for AI Agents
A captcha solver MCP server that lets AI agents solve reCAPTCHA, Cloudflare Turnstile, GeeTest and image captchas instead of stalling on them.
Works with Claude Desktop, Claude Code, Cursor, VS Code, and any Model Context Protocol client. Powered by CapSkip — a local captcha solver that runs on your own machine, licensed once rather than billed per solve.
npx -y capskip-mcpWhat this solves
An AI agent driving a browser hits a captcha and stops. This server gives it five tools so it can read the sitekey, solve the challenge, and carry on — without a human stepping in and without a per-solve API bill.
CapSkip runs as a desktop app exposing a captcha-solving HTTP API on 127.0.0.1:8080. capskip-mcp is a thin translation layer over that API: the fifth official CapSkip client, alongside the Python, Node.js, PHP and .NET SDKs.
Related MCP server: ma-browser
Supported captcha types
Captcha | Tool | Notes |
reCAPTCHA v2 solver (checkbox) |
| Returns a |
reCAPTCHA v2 invisible solver |
| Pass |
reCAPTCHA Enterprise solver |
| Pass |
reCAPTCHA v3 solver |
| Pass |
Cloudflare Turnstile solver |
| Widget and interstitial challenge pages |
GeeTest v3 solver |
| Slide puzzle; returns challenge/validate/seccode |
Image captcha solver (text/OCR) |
| File path, URL, data URI, or base64 |
Not supported: hCaptcha and FunCaptcha/Arkose. There is no tool for them and capskip_solve_recaptcha will not work on one. hCaptcha is the easiest to misidentify since it also carries a data-sitekey — check for class="h-captcha" or a js.hcaptcha.com script first.
Try them against live widgets on the captcha demo pages.
Quick start (5 minutes)
1. Install the CapSkip captcha solver
Download and run the CapSkip desktop app from capskip.com. Leave it running in the background.
In CapSkip settings, note the API port (default 8080) and API key (optional — if key validation is disabled, any string works).
2. Add capskip-mcp to your MCP client
No install step — npx fetches and runs it on demand.
{
"mcpServers": {
"capskip": {
"command": "npx",
"args": ["-y", "capskip-mcp"],
"env": {
"CAPSKIP_HOST": "127.0.0.1",
"CAPSKIP_PORT": "8080",
"CAPSKIP_API_KEY": "capskip"
}
}
}
}MCP client | Config file | Example |
Claude Desktop |
| |
Claude Code |
| |
Cursor |
| |
VS Code |
|
3. Restart your client
It should list five tools, all prefixed capskip_.
4. Ask your agent to solve a captcha
"Call capskip_status to confirm CapSkip is running, then solve the reCAPTCHA on this page and submit the form."
The agent reads the sitekey off the page, calls capskip_solve_recaptcha, and places the returned token in the page's g-recaptcha-response field.
Why a local captcha solver
Cloud captcha APIs bill per solve, so an agent that retries is an agent that costs money, and every page URL and sitekey you solve leaves your network.
CapSkip runs on your machine:
Unlimited captcha solving — licensed once, no per-solve fees, no credit balance to top up
Local by default — the solver talks to
127.0.0.1; nothing is proxied through a third-party queueNo rate limit per key — throughput is bounded by your machine, not a vendor's plan tier
Fast — image captchas return in well under a second; typical reCAPTCHA v2 solves land in 30–45s
Using an existing 2captcha or Anti-Captcha integration?
CapSkip exposes the familiar in.php / res.php endpoints, so it works as a 2captcha API alternative — point your existing client at 127.0.0.1:8080 and keep your code. See the migration notes. This MCP server is the equivalent for AI agents rather than scripts.
Tools
Tool | Purpose | Required arguments |
| Check whether the CapSkip desktop app is running and reachable | none |
| Read the text out of a distorted-text captcha image |
|
| Solve reCAPTCHA v2 or v3, including invisible and Enterprise |
|
| Solve a Cloudflare Turnstile widget or challenge page |
|
| Solve a GeeTest v3 slide-puzzle captcha |
|
There is no
min_scoreparameter oncapskip_solve_recaptcha. reCAPTCHA v3 scores are assigned by Google from signals no solver has access to — local or cloud, none can raise a score after the fact. Amin_scoreoption would promise control that does not exist, so it is deliberately left out. Passing it anyway is rejected as an unrecognized key, not silently ignored.
Full parameter tables and worked examples: API Reference.
Guide | Description |
Every captcha type — how to recognize it, what to read off the page, what call to make, where the answer goes | |
Full setup: CapSkip app, client config, first solve | |
Every tool, parameter, and return shape | |
Connection errors, timeouts, rejected tokens |
Browser automation: Playwright, Puppeteer and Selenium
This server solves the captcha and hands back a token; your agent's existing browser tooling does the driving. The pattern is the same whichever you use:
Read the sitekey from the page (
data-sitekey, or the widget's config object).Call the matching
capskip_solve_*tool with that sitekey and the page URL.Write the token into the response field and submit.
// The agent does this via its browser tool after capskip_solve_recaptcha returns
document.querySelector('#g-recaptcha-response').value = TOKEN;For non-agent scripts, use the language SDKs directly — see the Playwright, Puppeteer and Selenium guides.
Configuration
Variable | Default | Meaning |
|
| Any string when key validation is off |
|
| CapSkip host |
|
| API port from CapSkip settings |
|
| Default |
|
| Default |
|
| Max seconds between polls |
CLI flags override environment variables, which override the defaults:
capskip-mcp --api-key <key> --host <host> --port <port> --timeout <seconds> \
--recaptcha-timeout <seconds> --polling-interval <seconds>An invalid value (non-numeric port, port outside 1–65535, a negative or out-of-range timeout, an unknown flag) fails at startup naming the offending flag or variable, rather than surfacing later as a confusing solve failure.
What you get back
Every solve tool returns a human-readable text block and structuredContent matching its declared output schema:
{
"captchaId": "12345",
"code": "03AGdBq26f...",
"solveSeconds": 11.8
}capskip_solve_turnstileaddsuserAgent. Submit the token with this exact User-Agent — Cloudflare rejects a token replayed under a different one.capskip_solve_geetestaddschallenge,validateandseccode, to post back exactly as the site's own front-end would;codekeeps the raw JSON string CapSkip returns.
Long solves emit MCP progress notifications, so a 45-second reCAPTCHA does not trip your client's tool-call timeout.
Errors
Every tool call returns isError: true with readable text on failure — never a stack trace or a bare protocol error — so the model can read the message and correct course.
Cause | Message |
CapSkip unreachable |
|
Another process holds the port |
|
Wrong API key |
|
|
|
|
|
|
|
|
|
|
|
Solve exceeded |
|
Unknown or misspelled parameter | Rejected before the call reaches CapSkip, naming the key, e.g. |
See Troubleshooting for fixes.
FAQ
Can AI agents solve captchas?
Not on their own — a model cannot produce a valid reCAPTCHA or Turnstile token. It needs a solver. This MCP server connects your agent to CapSkip so it can request a real token and continue the task.
Does this work with Claude, Cursor and VS Code?
Yes. It is a standard MCP stdio server, so it works with any Model Context Protocol client, including Claude Desktop, Claude Code, Cursor and VS Code. Config examples for each are in examples/.
Is there a free captcha solver here?
The MCP server is MIT-licensed and free. It requires the CapSkip desktop app, which is licensed once and then solves without per-solve charges — unlike cloud APIs that bill per captcha.
Which captchas can it solve?
reCAPTCHA v2 (checkbox and invisible), reCAPTCHA v3, reCAPTCHA Enterprise, Cloudflare Turnstile, GeeTest v3, and image/text captchas. hCaptcha and FunCaptcha/Arkose are not supported.
Why does my reCAPTCHA v3 token get a low score?
Google assigns v3 scores from signals such as IP reputation and browsing history. A solver returns a valid token, but cannot raise the score. If a site enforces a high threshold, solve from a cleaner IP — a proxy is supported on the reCAPTCHA, Turnstile and GeeTest tools.
Does it need my captcha to be on a public page?
Yes for widget captchas — CapSkip loads the page URL you pass. Image captchas need only the image, which can be a local file.
Can I use it with Playwright or Puppeteer?
Yes. The agent drives the browser; this server supplies the token. See the browser automation section.
Requirements
Node.js 18 or newer
The CapSkip desktop app installed and running (download)
Links
Captcha demo pages — live reCAPTCHA, Turnstile, GeeTest and image widgets
License
MIT — see LICENSE.
Available Tools
5 toolscapskip_solve_geetestSolve GeeTest v3A
Solve a GeeTest v3 slide-puzzle captcha. Returns geetest_challenge, geetest_validate, and geetest_seccode to post back exactly as the site's own front-end would. IMPORTANT: the challenge value is single-use and expires in roughly a minute, so fetch gt and challenge from the page immediately before calling. A stale challenge is the most common failure.
| Name | Required | Description | Default |
|---|---|---|---|
| gt | Yes | The gt value. Static per site, so it can be reused. | |
| url | Yes | Full URL of the page the captcha appears on, including scheme. | |
| proxy | No | Solve through this proxy so the answer is produced from its IP. | |
| timeout | No | Seconds to wait before giving up. Maximum 600. | |
| challenge | Yes | The challenge value. Single-use and expires in about a minute — fetch a fresh one immediately before calling this. | |
| api_server | No | A non-default GeeTest API domain, e.g. 'api-na.geetest.com'. |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| seccode | No | |
| validate | No | |
| captchaId | Yes | |
| challenge | No | |
| solveSeconds | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No contradiction with annotations (readOnlyHint=false, destructiveHint=false). Description adds valuable behavioral context beyond annotations, such as single-use challenge expiry, the need for immediate fetching, and that results should be posted back like the site's own front-end. This enhances transparency about failure modes and usage constraints.
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?
Description is three sentences, front-loaded with the core action and return values. It includes an important usage warning without unnecessary elaboration, making every sentence purposeful.
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 six parameters, output schema, and annotations, the description covers the key operational context: what the tool solves, what returns, and the critical freshness requirement. It does not discuss proxy usage or timeout, but those are well-documented in the schema, so the description is sufficiently complete for typical use.
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?
Schema description coverage is 100%, with detailed descriptions for all 6 parameters. The description reinforces the challenge freshness warning and gt reuse but adds minimal new meaning beyond the schema. Baseline of 3 is appropriate since the schema does the heavy lifting.
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?
Description clearly states 'Solve a GeeTest v3 slide-puzzle captcha', naming the specific captcha type and resource. It also specifies return values (geetest_challenge, geetest_validate, geetest_seccode), distinguishing it from sibling captcha-solving tools like reCAPTCHA and Turnstile.
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?
Provides explicit operational guidance: 'fetch gt and challenge from the page immediately before calling' and warns that a stale challenge is the most common failure. It does not explicitly contrast with alternative siblings, but the captcha-type-specific name and description give clear context for when this tool is appropriate.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capskip_solve_image_captchaSolve an image captchaA
Read the text out of a distorted-text captcha image. Returns the recognized text, which you type into the page's captcha field. Proxies are not supported for image captchas.
| Name | Required | Description | Default |
|---|---|---|---|
| image | Yes | The captcha image: a local file path, an http(s) URL, a data: URI, or a raw base64 string. | |
| timeout | No | Seconds to wait before giving up. Maximum 600. |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| captchaId | Yes | |
| solveSeconds | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With annotations already indicating readOnlyHint=false and destructiveHint=false, the description adds useful behavioral context: it returns recognized text and notes that proxies are unsupported. This goes beyond the structured annotations without contradicting them, providing operational expectations for the agent.
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 two sentences, front-loaded with the primary action and immediate use case. The second sentence provides a necessary limitation (proxy support) without any filler or redundancy. Every word contributes to understanding the tool's function and constraints.
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 simple parameter set (2 params, 1 required), full schema coverage, presence of an output schema, and annotations, the description covers the essential behavior, return value, and a key limitation. It could explicitly contrast with sibling captcha-solving tools, but the tool name and sibling list sufficiently fill that gap, making the description complete for the tool's scope.
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 covers 100% of parameters with detailed descriptions for 'image' and 'timeout'. The description only reiterates that the image is a captcha, which is already evident from the schema. With full schema coverage, the baseline of 3 is appropriate; the description adds no significant semantic value 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 clearly states the action: 'Read the text out of a distorted-text captcha image' with a specific resource and outcome. It distinguishes this tool from siblings by explicitly focusing on 'image captcha' versus Turnstile, reCAPTCHA, and Geetest, making the purpose unambiguous.
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 implies when to use it: when a distorted-text image captcha needs solving, and explains the result should be typed into the page's captcha field. It also provides a clear exclusion: 'Proxies are not supported for image captchas.' It does not explicitly name alternatives, but the sibling tool names and the 'image captcha' qualifier offer sufficient differentiation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capskip_solve_recaptchaSolve reCAPTCHAA
Solve a Google reCAPTCHA v2 or v3 widget, including invisible and Enterprise variants. Returns a token to place in the page's "g-recaptcha-response" field before submitting the form. Read the sitekey from the page first — a guessed sitekey fails. Note that reCAPTCHA v3 returns a score assigned by Google; no solver can raise it.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full URL of the page the captcha appears on, including scheme. | |
| proxy | No | Solve through this proxy so the token is issued against its IP. | |
| action | No | v3 only. The action passed to grecaptcha.execute(), e.g. 'login'. | |
| data_s | No | v2 only. The data-s value, used by Google's own services. Rarely needed — CapSkip rejects it on a v3 submit. | |
| sitekey | Yes | The site key, from the widget's data-sitekey attribute or the grecaptcha config. | |
| timeout | No | Seconds to wait before giving up. Maximum 600. | |
| version | No | Which reCAPTCHA generation the page uses. Defaults to v2. | |
| invisible | No | v2 only. True when the widget renders with size=invisible. | |
| enterprise | No | True for reCAPTCHA Enterprise. Works with both v2 and v3. |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| captchaId | Yes | |
| solveSeconds | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already mark the tool as non-readonly, non-destructive, and open-world. The description adds useful behavioral context: the token is placed in g-recaptcha-response before form submission, guessed sitekeys fail, and v3 scores are immutable. It does not describe potential external service requests or rate limits, but the openWorldHint and schema largely cover the interaction model.
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 three sentences and about 70 words, with no filler or repetition of schema details. It front-loads the main purpose, then packs in the key practical warnings. Every sentence contributes new information.
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 complexity (9 parameters, nested proxy object, output schema) and the exhaustive input schema, the description covers all essential operational context: what it solves, what it returns, a critical prerequisite, and a fundamental limitation. It does not need to explain return values because an output schema exists, and it complements the rich schema and annotations well.
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?
Schema description coverage is 100%, so a baseline of 3 applies. The description adds meaningful parameter guidance beyond the schema by stressing that the sitekey must be read from the page (not guessed) and by noting v3's score cannot be raised, which affects expectations for the version/action parameters. This extra context justifies a score above baseline.
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 opens with a specific verb and resource: 'Solve a Google reCAPTCHA v2 or v3 widget, including invisible and Enterprise variants.' It clearly distinguishes itself from sibling tools (Turnstile, image captcha, Geetest) by naming Google reCAPTCHA and describing what it produces. The returned token's placement in g-recaptcha-response further clarifies its purpose.
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 a concrete prerequisite: 'Read the sitekey from the page first — a guessed sitekey fails.' It also warns about the v3 score limitation, helping agents know not to expect a higher score. It lacks an explicit 'use this instead of X' statement, but the sibling tool names and captcha-specific language make the context clear enough.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capskip_solve_turnstileSolve Cloudflare TurnstileA
Solve a Cloudflare Turnstile widget or interstitial challenge page. Returns a token for the page's "cf-turnstile-response" field. IMPORTANT: submit the token using the returned userAgent — Cloudflare rejects a token replayed under a different User-Agent. For an interstitial challenge page, also pass cdata and pagedata read from the page.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Full URL of the page the captcha appears on, including scheme. | |
| cdata | No | The cData value. Interstitial challenge pages only, not ordinary widgets. | |
| proxy | No | Solve through this proxy so the token is issued against its IP. | |
| action | No | The action from data-action or turnstile.render(). | |
| sitekey | Yes | The Turnstile site key, from the widget's data-sitekey attribute. | |
| timeout | No | Seconds to wait before giving up. Maximum 600. | |
| pagedata | No | The chlPageData value. Interstitial challenge pages only. |
Output Schema
| Name | Required | Description |
|---|---|---|
| code | Yes | |
| captchaId | Yes | |
| userAgent | No | |
| solveSeconds | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
It discloses a critical behavioral constraint: the returned token must be submitted with the same userAgent or Cloudflare rejects it. It also clarifies when cdata/pagedata are required. These go beyond the annotations (readOnlyHint=false, openWorldHint=true) and are essential for correct use.
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?
Three tightly written sentences immediately convey purpose, output, and a high-priority caveat. No filler or repetition of schema fields; every sentence adds value.
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 7-parameter solver with a nested proxy object and an output schema, the description covers the essential behavioral nuances (widget vs interstitial, token-userAgent binding). The schema documents parameter details, and the output schema removes the need to explain return values, making the description complete for this complexity.
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 already describes all seven parameters with 100% coverage, giving a solid baseline. The description adds extra meaning by tying cdata/pagedata to the interstitial challenge page scenario and explaining the userAgent token requirement, though it does not detail proxy or timeout semantics 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 opens with a specific verb ('Solve') and resource ('Cloudflare Turnstile widget or interstitial challenge page'), and explicitly states the output (a token for cf-turnstile-response). This clearly distinguishes it from sibling captcha-solving tools (image, recaptcha, geetest).
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 clear usage context by distinguishing between widget and interstitial challenge page forms, and instructs passing cdata/pagedata for interstitial pages. It does not explicitly name alternatives or exclusions, but the sibling names make the intended use obvious.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
capskip_statusCheck CapSkip statusARead-only
Check whether the CapSkip desktop app is running and reachable. Call this first when a solve fails unexpectedly, to tell "CapSkip is not running" apart from "the sitekey was wrong". Takes no arguments.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Output Schema
| Name | Required | Description |
|---|---|---|
| host | Yes | |
| port | Yes | |
| detail | Yes | |
| latencyMs | No | |
| reachable | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and openWorldHint=true, so the description adds value by specifying what is being checked (running and reachable) and the diagnostic purpose. It does not introduce any surprising behavior, and there is no contradiction with annotations.
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 two sentences, front-loaded with the core purpose, and includes essential usage guidance. Every sentence contributes value with no redundancy.
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 simple status check with no parameters, an output schema, and read-only annotations, the description fully covers what the tool does, when to use it, and that it takes no arguments. No gaps remain.
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 tool takes no parameters, and the description explicitly states 'Takes no arguments,' which matches the empty schema. Baseline for 0 params is 4, and since no additional semantic detail is needed, this is appropriate.
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 tool checks whether the CapSkip desktop app is running and reachable, using a specific verb and resource. It also distinguishes itself from sibling solving tools by framing this as a diagnostic pre-check.
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?
Explicit usage guidance is provided: 'Call this first when a solve fails unexpectedly' and it distinguishes between 'CapSkip is not running' and 'the sitekey was wrong'. This gives clear when-to-use context without needing to mention alternatives.
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.
5 tool updates
v1.0.0- First observed
capskip_solve_geetest - First observed
capskip_solve_image_captcha - First observed
capskip_solve_recaptcha - First observed
capskip_solve_turnstile - First observed
capskip_status
TDQS
Each tool targets a distinct captcha type or supporting action. capskip_solve_turnstile, capskip_solve_recaptcha, capskip_solve_image_captcha, and capskip_solve_geetest are clearly separated by captcha vendor/type, while capskip_status serves a unique diagnostic role. There is no overlap or ambiguity between them.
All tools share the capskip prefix and are snake_case, with the four solving tools following a clear 'capskip_solve_<type>' pattern. capskip_status deviates from this pattern but is consistent with the prefix convention and represents a distinct action, so the inconsistency is minor.
Five tools is well-scoped for a captcha-solving server. Each tool serves a necessary role covering the major captcha types plus a status check, and there is no bloat or missing essential operation for the stated purpose.
The tool surface comprehensively covers the main captcha solving workflows: Turnstile, reCAPTCHA, image captcha, and GeeTest, along with a status check for operational reliability. No obvious dead ends or critical gaps exist within the captcha-solving domain.
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curl -X GET 'https://glama.ai/api/mcp/v1/servers/capskip/capskip-mcp'
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