# AI Source Verifier (`ficuslink/ai-source-verifier`) Actor MCP server that visits URLs cited by AI assistants and compares claimed numbers, dates, and facts against actual page content. Surfaces discrepancies and recovers dead links via Wayback Machine. - **URL**: https://apify.com/ficuslink/ai-source-verifier.md - **Developed by:** [KIM SEUNG KOOK](https://apify.com/ficuslink) (community) - **Categories:** MCP servers, AI, Agents - **Stats:** 1 total users, 1 monthly users, 0.0% runs succeeded, NaN bookmarks - **User rating**: No ratings yet ## Pricing from $10.00 / 1,000 source verifications This Actor is paid per event and usage. You are charged both the fixed price for specific events and for Apify platform usage. Learn more: https://docs.apify.com/platform/actors/running/actors-in-store#pay-per-event ## What's an Apify Actor? Actors are a software tools running on the Apify platform, for all kinds of web data extraction and automation use cases. In Batch mode, an Actor accepts a well-defined JSON input, performs an action which can take anything from a few seconds to a few hours, and optionally produces a well-defined JSON output, datasets with results, or files in key-value store. In Standby mode, an Actor provides a web server which can be used as a website, API, or an MCP server. Actors are written with capital "A". ## How to integrate an Actor? If asked about integration, you help developers integrate Actors into their projects. You adapt to their stack and deliver integrations that are safe, well-documented, and production-ready. The best way to integrate Actors is as follows. In JavaScript/TypeScript projects, use official [JavaScript/TypeScript client](https://docs.apify.com/api/client/js.md): ```bash npm install apify-client ``` In Python projects, use official [Python client library](https://docs.apify.com/api/client/python.md): ```bash pip install apify-client ``` In shell scripts, use [Apify CLI](https://docs.apify.com/cli/docs.md): ````bash # MacOS / Linux curl -fsSL https://apify.com/install-cli.sh | bash # Windows irm https://apify.com/install-cli.ps1 | iex ```bash In AI frameworks, you might use the [Apify MCP server](https://docs.apify.com/platform/integrations/mcp.md). If your project is in a different language, use the [REST API](https://docs.apify.com/api/v2.md). For usage examples, see the [API](#api) section below. For more details, see Apify documentation as [Markdown index](https://docs.apify.com/llms.txt) and [Markdown full-text](https://docs.apify.com/llms-full.txt). # README ## AI Source Verifier An MCP server that visits URLs cited by AI assistants and shows what the sources actually say. It compares claimed numbers, dates, and facts against real page content — so the AI can self-correct before delivering an answer. **No LLM inside.** Linden extracts data deterministically (HTML parsing, regex, BM25 scoring). The AI decides what to do with it. ### What it does - **Dead link detection** — checks if each URL is alive, dead, or access-restricted - **Numeric/date comparison** — extracts numbers and dates from the page and compares them against the AI's claim - **Relevant snippet extraction** — uses BM25 scoring with multilingual tokenization (English, Korean, Japanese, Chinese) - **Wayback Machine recovery** — finds archived versions of dead pages automatically - **Page freshness** — reports `age_days` and `last_modified` when available - **Honest reporting** — clearly marks paywalled, blocked, and unsupported content instead of guessing ### How to connect This Actor runs as an MCP server in [Standby mode](https://docs.apify.com/platform/actors/running/standby). Connect it to any MCP-compatible AI client. #### Claude Desktop (Windows) Install `mcp-remote` globally (`npm install -g mcp-remote`), then add to your Claude Desktop config: ```json { "mcpServers": { "linden": { "command": "mcp-remote", "args": [ "--header", "Authorization: Bearer YOUR_APIFY_TOKEN", "https://ficuslink--ai-source-verifier.apify.actor/mcp" ] } } } ```` #### Direct HTTP Send MCP requests via POST to the Standby endpoint: ``` POST https://ficuslink--ai-source-verifier.apify.actor/mcp Authorization: Bearer YOUR_APIFY_TOKEN Content-Type: application/json ``` ### Input The `linden_check` tool accepts an array of sources (1-50 URLs per call): ```json { "sources": [ { "url": "https://www.investing.com/currencies/usd-krw", "claim": "USD/KRW exchange rate is 1,385" }, { "url": "https://www.reuters.com/markets/currencies/won-weakens", "claim": "The Korean won weakened past 1,390 per dollar" }, { "url": "https://example.com/stats" } ] } ``` - `url` (required): The URL to verify. HTTP and HTTPS only. - `claim` (optional): The specific fact the AI is asserting based on this URL. Including a claim enables numeric comparison and targeted snippet extraction. Write the claim in the same language as the source page for best results. ### Output Each result includes a `verdict` and relevant fields depending on the outcome. - `language_mismatch`: Set to `true` when the claim language differs from the page language. Numeric/date comparison still works; snippet accuracy may be reduced. - `accessible_content`: `"title_only"` for paywalled pages, `"none"` for robots.txt-blocked pages. - `archive_url` / `archive_date`: Wayback Machine snapshot URL and date (YYYYMMDD) for dead pages. - `error_message`: Human-readable error description for `error` and `timeout` verdicts. ```json { "summary": { "matched": 1, "mismatch": 1, "recovered": 1, "restricted": 1, "unchecked": 0, "unavailable": 0, "unsupported": 0, "timeout": 0, "error": 0 }, "results": [ { "url": "https://www.investing.com/currencies/usd-krw", "status": "alive", "http_code": 200, "page_title": "USD/KRW - US Dollar Korean Won", "last_modified": "2026-03-26", "age_days": 1, "snippet": "USD/KRW 1,391.50 +3.20 (+0.23%)", "snippet_score": 8.7, "snippet_confidence": "high", "claimed_values": ["1,385"], "found_values": ["1,391.50"], "verdict": "mismatch" }, { "url": "https://www.reuters.com/markets/currencies/won-weakens", "status": "alive", "http_code": 200, "page_title": "Korean won hits 3-month low as trade tensions mount", "snippet": "The Korean won weakened past 1,390 per dollar on Monday...", "snippet_score": 7.2, "snippet_confidence": "high", "claimed_values": ["1,390"], "found_values": ["1,390"], "verdict": "matched" }, { "url": "https://old-finance-blog.kr/bok-rate-decision", "status": "dead", "http_code": 404, "archive_url": "https://web.archive.org/web/20260310/old-finance-blog.kr/bok-rate-decision", "archive_date": "20260310", "verdict": "recovered" }, { "url": "https://www.bloomberg.com/news/articles/2026-03-krw-forecast", "status": "restricted", "http_code": 403, "page_title": "Won Forecast: Analysts See Further Weakness Ahead", "accessible_content": "title_only", "verdict": "restricted" } ] } ``` ### Verdict types | Verdict | Meaning | Billed | |---------|---------|--------| | `matched` | Claimed values found on the page | Yes | | `mismatch` | Values differ from what was claimed | Yes | | `unchecked` | No claim provided; page title and description returned | Yes | | `recovered` | Page is dead but content found in Wayback Machine archive | Yes | | `unavailable` | Page is dead and no archive exists | Yes | | `restricted` | Paywall or login required (title only) / robots.txt blocked | Paywall: Yes / robots.txt: No | | `unsupported` | Content type not supported (PDF, images, etc.) | No | | `timeout` | Request timed out | No | | `error` | Unexpected error during processing | No | ### Supported value formats Numeric and date extraction supports four languages. Snippet tokenization uses `Intl.Segmenter` for English, Korean, Japanese, and Chinese. | Type | Examples | |------|----------| | Numbers | 1,391.50 / 1,391 | | Percentages | 3.5% / 3.5퍼센트 / 3.5パーセント / 3.5percent | | Currency (symbols) | $1,500 / €1,500 / £1,500 / ¥1,500 | | Currency (Korean) | 1,500원 | | Currency (CJK) | 1,500元 / 1,500円 | | Abbreviated | $1.5T / $1.5B / $1.5M / $1.5K | | Korean large units | 1.5조원 / 500억 / 3000만 | | CJK large units | 1.5兆 / 17.96万亿元 / 500万円 / 1.5亿元 | | Dates (ISO) | 2026-03-26 | | Dates (English) | March 26, 2026 | | Dates (Korean) | 2026년 3월 26일 | | Dates (CJK) | 2026年3月26日 | ### Limitations - Does not detect subtle meaning distortion or exaggeration - Does not perform full fact-checking — it surfaces data, not judgments - Cannot access paywalled content (reports `restricted` with title only) - PDF content verification is not supported in this version - Cross-language semantic matching is limited; numeric/date comparison works across languages ### Pricing **$0.01 per call** (up to 50 URLs per call). A call is billed only when it produces at least one meaningful result. Results with `error`, `timeout`, `unsupported`, or `restricted` (robots.txt) verdicts are not billed. If every URL in a call falls into these categories, the call is free. Estimated total cost per call (including Apify infrastructure): ~$0.03-0.04 on the Starter plan. ### Security This Actor visits arbitrary URLs provided by AI assistants. Security is built in from the ground up: - **SSRF defense (4 layers)**: Input validation for IP literals, DNS pinning for HTTP requests, pre-navigation DNS re-verification for Playwright, and real-time request monitoring via `page.route('**/*')` - **HTTP/2 disabled**: Prevents connection pooling from bypassing DNS pinning - **Resource limits**: 10MB response cap, 30s per-URL timeout, 5 redirect hops max, decompression bomb protection - **robots.txt compliance**: Checked before crawling each domain. Blocked pages receive `restricted` verdict with no charge. - **Identifiable User-Agent**: `Linden/1.0 (AI Source Verifier by FICUSLINK; +https://ficuslink.com)` ### Disclaimer This tool surfaces discrepancies between AI claims and source content. It is not a substitute for professional fact-checking. Results are provided as-is without warranty of completeness or accuracy. # Actor input Schema ## Actor input object example ```json {} ``` # API You can run this Actor programmatically using our API. Below are code examples in JavaScript, Python, and CLI, as well as the OpenAPI specification and MCP server setup. ## JavaScript example ```javascript import { ApifyClient } from 'apify-client'; // Initialize the ApifyClient with your Apify API token // Replace the '' with your token const client = new ApifyClient({ token: '', }); // Prepare Actor input const input = {}; // Run the Actor and wait for it to finish const run = await client.actor("ficuslink/ai-source-verifier").call(input); // Fetch and print Actor results from the run's dataset (if any) console.log('Results from dataset'); console.log(`💾 Check your data here: https://console.apify.com/storage/datasets/${run.defaultDatasetId}`); const { items } = await client.dataset(run.defaultDatasetId).listItems(); items.forEach((item) => { console.dir(item); }); // 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/js/docs ``` ## Python example ```python from apify_client import ApifyClient # Initialize the ApifyClient with your Apify API token # Replace '' with your token. client = ApifyClient("") # Prepare the Actor input run_input = {} # Run the Actor and wait for it to finish run = client.actor("ficuslink/ai-source-verifier").call(run_input=run_input) # Fetch and print Actor results from the run's dataset (if there are any) print("💾 Check your data here: https://console.apify.com/storage/datasets/" + run["defaultDatasetId"]) for item in client.dataset(run["defaultDatasetId"]).iterate_items(): print(item) # 📚 Want to learn more 📖? Go to → https://docs.apify.com/api/client/python/docs/quick-start ``` ## CLI example ```bash echo '{}' | apify call ficuslink/ai-source-verifier --silent --output-dataset ``` ## MCP server setup ```json { "mcpServers": { "apify": { "command": "npx", "args": [ "mcp-remote", "https://mcp.apify.com/?tools=ficuslink/ai-source-verifier", "--header", "Authorization: Bearer " ] } } } ``` ## OpenAPI specification ```json { "openapi": "3.0.1", "info": { "title": "AI Source Verifier", "description": "MCP server that visits URLs cited by AI assistants and compares claimed numbers, dates, and facts against actual page content. Surfaces discrepancies and recovers dead links via Wayback Machine.", "version": "1.0", "x-build-id": "jNLiXYezP1C6Klesv" }, "servers": [ { "url": "https://api.apify.com/v2" } ], "paths": { "/acts/ficuslink~ai-source-verifier/run-sync-get-dataset-items": { "post": { "operationId": "run-sync-get-dataset-items-ficuslink-ai-source-verifier", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for its completion, and returns Actor's dataset items in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } }, "/acts/ficuslink~ai-source-verifier/runs": { "post": { "operationId": "runs-sync-ficuslink-ai-source-verifier", "x-openai-isConsequential": false, "summary": "Executes an Actor and returns information about the initiated run in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK", "content": { "application/json": { "schema": { "$ref": "#/components/schemas/runsResponseSchema" } } } } } } }, "/acts/ficuslink~ai-source-verifier/run-sync": { "post": { "operationId": "run-sync-ficuslink-ai-source-verifier", "x-openai-isConsequential": false, "summary": "Executes an Actor, waits for completion, and returns the OUTPUT from Key-value store in response.", "tags": [ "Run Actor" ], "requestBody": { "required": true, "content": { "application/json": { "schema": { "$ref": "#/components/schemas/inputSchema" } } } }, "parameters": [ { "name": "token", "in": "query", "required": true, "schema": { "type": "string" }, "description": "Enter your Apify token here" } ], "responses": { "200": { "description": "OK" } } } } }, "components": { "schemas": { "inputSchema": { "type": "object", "properties": {} }, "runsResponseSchema": { "type": "object", "properties": { "data": { "type": "object", "properties": { "id": { "type": "string" }, "actId": { "type": "string" }, "userId": { "type": "string" }, "startedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "finishedAt": { "type": "string", "format": "date-time", "example": "2025-01-08T00:00:00.000Z" }, "status": { "type": "string", "example": "READY" }, "meta": { "type": "object", "properties": { "origin": { "type": "string", "example": "API" }, "userAgent": { "type": "string" } } }, "stats": { "type": "object", "properties": { "inputBodyLen": { "type": "integer", "example": 2000 }, "rebootCount": { "type": "integer", "example": 0 }, "restartCount": { "type": "integer", "example": 0 }, "resurrectCount": { "type": "integer", "example": 0 }, "computeUnits": { "type": "integer", "example": 0 } } }, "options": { "type": "object", "properties": { "build": { "type": "string", "example": "latest" }, "timeoutSecs": { "type": "integer", "example": 300 }, "memoryMbytes": { "type": "integer", "example": 1024 }, "diskMbytes": { "type": "integer", "example": 2048 } } }, "buildId": { "type": "string" }, "defaultKeyValueStoreId": { "type": "string" }, "defaultDatasetId": { "type": "string" }, "defaultRequestQueueId": { "type": "string" }, "buildNumber": { "type": "string", "example": "1.0.0" }, "containerUrl": { "type": "string" }, "usage": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "integer", "example": 1 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } }, "usageTotalUsd": { "type": "number", "example": 0.00005 }, "usageUsd": { "type": "object", "properties": { "ACTOR_COMPUTE_UNITS": { "type": "integer", "example": 0 }, "DATASET_READS": { "type": "integer", "example": 0 }, "DATASET_WRITES": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_READS": { "type": "integer", "example": 0 }, "KEY_VALUE_STORE_WRITES": { "type": "number", "example": 0.00005 }, "KEY_VALUE_STORE_LISTS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_READS": { "type": "integer", "example": 0 }, "REQUEST_QUEUE_WRITES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_INTERNAL_GBYTES": { "type": "integer", "example": 0 }, "DATA_TRANSFER_EXTERNAL_GBYTES": { "type": "integer", "example": 0 }, "PROXY_RESIDENTIAL_TRANSFER_GBYTES": { "type": "integer", "example": 0 }, "PROXY_SERPS": { "type": "integer", "example": 0 } } } } } } } } } } ```