AIDataParser

io.github.shibley由 GitHub 账号 shibley 发布v0.2.0更新于 Oct 24, 2026

PDFs, images and messy text to schema-guaranteed JSON. try_parse runs a real extraction, no key.

发布方自己的服务：Parser Club

已验证Streamable HTTP可网页运行文件与存储数据与分析

服务详情

标识符: io.github.shibley/aidataparser
传输: Streamable HTTP
运行时: Web executable
信任: Verified
发布于: Sep 22, 2026

安全提示

MCP 服务会接收对话中的工具调用请求，并可能执行外部操作。启用前请先了解该服务能做什么，并只授予它所需的权限。

注册中心已验证此条目所属的 GitHub 账号 shibley。这并不表明该账号就是产品方。

SourceWeft 的检查只涵盖条目是否完整、端点是否响应；不审查服务器的代码，也不审查其工具的行为。

在 README 中添加徽章

向读者展示该 MCP 服务已收录于 SourceWeft，徽章链接到本页。

[![Listed on SourceWeft](https://sourceweft.com/badge/mcp/io.github.shibley%2Faidataparser.svg)](https://sourceweft.com/mcp/io.github.shibley%2Faidataparser?utm_source=readme&utm_medium=badge)

概览

AI 生成的概览

AIDataParser 是一个托管式 MCP 服务器，可将 PDF、图片和杂乱文本转换为符合 schema 的 JSON，提供免费试用提取和按积分计费的付费解析。

可以做什么: 对最多 4000 字符的文本运行免费试用提取，无需密钥或账号即可预览输出结构，每天限 3 次。从通过 URL 或 base64 提供的 PDF、图片中提取受 schema 约束的 JSON，也可从抓取网页、邮件正文、聊天记录或 OCR 结果等原始杂乱文本中提取。根据一份样本文档推断可复用的 JSON Schema，并列出内置模板（如发票、收据、简历）。按 schema 或内置模板校验 JSON 对象并返回逐字段错误。通过邮箱创建 API 密钥、查询剩余积分，并获取积分包的 Stripe 结账链接。
适用场景: 当助手需要把发票、收据、简历、扫描文档或非结构化文本转换为遵循固定 schema 的结构化 JSON 时使用，也适合在付费前先测试提取质量。它面向文档处理和数据录入流程，而非通用文件存储或搜索。
运行要求: 远程 Streamable HTTP 端点，无需本地运行时或安装包。免费工具 try_parse、list_schemas 和 validate 无需密钥。付费工具需要 AIDataParser API 密钥，可通过 create_api_key 提供邮箱获取，或使用密钥接口，并以 Authorization Bearer 请求头配置。每份文档消耗积分。

安装前请注意

create_api_key 需要用户邮箱并返回有效 API 密钥，应将该密钥视为机密。parse_document 和 parse_text 会把文档内容或文本发送给第三方服务，且每次消耗 1 积分。buy_credits 返回真实付款的 Stripe 结账链接，购买的积分会记入所配置密钥的账户。免费试用每天限 3 次。

安装

在 SourceWeft 中

打开控制台中的 AIDataParser，将其添加到工作区。
为需要使用其工具的对话启用该服务。

Web executable，通过 Streamable HTTP。远程服务在工作区中配置后即可从网页运行时运行。

交给智能体安装

把这段提示词粘贴到 Claude Code、Codex、Cursor 等智能体，或 SourceWeft 对话中。智能体会读取该服务器的安装指南，先向你展示发布者、端点和登录方式，经你同意后再把它添加到你的客户端。密钥不会写进任何命令。

阅读 https://sourceweft.com/mcp/io.github.shibley%2Faidataparser/install.md，并按其中说明把这个 MCP 服务器接入我的客户端。修改任何配置之前，先告诉我它的发布者、端点和登录方式，等我确认。不要把 API 密钥写进命令或我会提交的文件；问我密钥应从哪里获取。

查看智能体所依据的安装指南

其他 MCP 客户端

把它添加到你客户端的 mcpServers 配置中。

{
  "mcpServers": {
    "aidataparser": {
      "type": "http",
      "url": "https://aidataparser.com/v1/mcp"
    }
  }
}

README

AIDataParser MCP server

The official Model Context Protocol registry record for AIDataParser — a credit-based data-extraction API that turns PDFs, images and messy text into schema-guaranteed JSON.

There is no server code in this repo. The MCP server is hosted: it lives at https://aidataparser.com/v1/mcp and speaks JSON-RPC 2.0 over Streamable HTTP. This repo holds the server.json that is the source of our record in registry.modelcontextprotocol.io, the canonical upstream every downstream MCP catalog syncs from.

Add it to your client

json

{  "mcpServers": {    "aidataparser": {      "type": "http",      "url": "https://aidataparser.com/v1/mcp",      "headers": { "Authorization": "Bearer adp_live_..." }    }  }}

{  "mcpServers": {    "aidataparser": {      "type": "http",      "url": "https://aidataparser.com/v1/mcp",      "headers": { "Authorization": "Bearer adp_live_..." }    }  }}

Try it before you sign up. try_parse runs a real extraction with no key, no email and no account — up to 4,000 characters of text, 3 calls per day. Add the server without the headers block and call it:

json

{ "name": "try_parse", "arguments": { "text": "INVOICE #1042 ... Total due $1,240.00", "schema_id": "invoice" } }

{ "name": "try_parse", "arguments": { "text": "INVOICE #1042 ... Total due $1,240.00", "schema_id": "invoice" } }

When you want more, get a key (50 free credits, no card) — over MCP with the create_api_key tool, or:

bash

curl -X POST https://aidataparser.com/v1/keys \  -H 'Content-Type: application/json' \  -d '{"email":"[email protected]"}'

curl -X POST https://aidataparser.com/v1/keys \  -H 'Content-Type: application/json' \  -d '{"email":"[email protected]"}'

Tools

Tool	Cost	What it does
`try_parse`	free, no key	Real extraction on ≤4,000 chars of text, 3/day — see the output before signing up
`create_api_key`	free, no key	An email → a live `adp_live_` key with 50 free credits
`parse_document`	1 credit	PDF or image (`url` or `base64`) → JSON matching your schema
`parse_text`	1 credit	Raw/messy text → JSON matching your schema
`infer_schema`	1 credit	One sample → a reusable JSON Schema
`validate`	free, no key	Check a JSON value against a schema
`check_credits`	free	Credits remaining on the key
`list_schemas`	free, no key	Built-in templates (invoice, receipt, resume, …)

Credit packs: https://aidataparser.com/pricing

Publishing

.github/workflows/publish-mcp.yml publishes on a push to main using GitHub OIDC — no secrets. Bump version in server.json to cut a release; a push that does not change the version is a no-op.

Before it publishes, the workflow runs two gates:

npm test — static checks on server.json (validate-server-json.mjs). Each rule maps to a real failure from a sibling repo, e.g. the registry's 100-char description cap that 422'd aisotools-mcp-server v0.1.0.
npm run check:remote — a live initialize + tools/list handshake against the URL about to be advertised. A registry record pointing at a dead endpoint is worse than no record.

Both are runnable locally.

来源：README.md，提交 0f4d885

工具

try_parse

Try it now — parse text into JSON with no API key

Run a REAL extraction with no API key, no email and no signup, so you can see the output shape before committing to anything. Pass up to 4000 characters of messy text in `text` (an invoice, a receipt, a resume, scraped HTML, an email body) and optionally a `schema` or `schema_id` to constrain the result. Returns the same structured data, confidence and review_needed flag the paid tools return. Limited to 3 calls per caller per day — for real volume call create_api_key for 50 free credits, then use parse_text or parse_document.

输入参数text必填schemaschema_idinstructions

create_api_key

Get an API key with free credits

Start here if you do not have an AIDataParser API key. Provide the user's `email` and receive a live adp_live_ API key with 50 free credits — no card, no signup form. Configure it on this MCP server as `Authorization: Bearer <api_key>` to unlock parse_document, parse_text and infer_schema. The key is returned ONCE and is never shown again, so surface it to the user and store it. Ask the user for their address; do not invent one. Free — does not consume a credit.

输入参数email必填

parse_document

Parse a document into structured JSON

Extract clean, schema-guaranteed JSON from a PDF or image. Provide the document via `url` or `base64`. Pass an optional JSON `schema` to constrain the output shape, and `instructions` to guide extraction. Returns the extracted data plus a confidence score and a review_needed flag. Costs 1 credit per successful call.

输入参数urlbase64redactschemaschema_idmedia_typeinstructions

parse_text

Parse raw text into structured JSON

Extract clean, schema-guaranteed JSON from raw/messy text you already have — scraped web content, email bodies, chat logs, OCR output, or pasted tables. Pass the text in `text`. Use this instead of parse_document when you don't have a file. Optional JSON `schema` (or `schema_id`) constrains the output shape and `instructions` guides extraction. Returns the extracted data plus a confidence score and a review_needed flag. Costs 1 credit per successful call.

输入参数text必填redactschemaschema_idinstructions

infer_schema

Infer a reusable JSON Schema from a sample

Given one sample document's `text`, propose a reusable JSON Schema for that document type. Use this when no built-in schema_id fits: infer a schema once, review it, then reuse it as `schema` on parse_document / parse_text across many documents for consistent output. Returns the JSON Schema plus a flat field list and an inferred doc_type. Costs 1 credit per successful call.

输入参数text必填doc_typeinstructions

validate

Validate JSON against a schema

Check whether a JSON object conforms to a JSON `schema` (or a built-in `schema_id` template) and get back a valid flag plus per-field errors. Use this to verify data you already hold — a prior parse result, your own output, or an upstream feed — before acting on it or spending a credit. Deterministic, free, and needs no API key.

输入参数data必填schemaschema_id

check_credits

Check remaining credits

Return the number of extraction credits remaining on the authenticated API key. Free — does not consume a credit.

无需输入参数。

list_schemas

List built-in schema templates

Return the built-in schema templates you can pass to parse_document as `schema_id` (invoice, receipt, resume, etc.), each with its id and the fields it extracts. Free — does not consume a credit and needs no API key.

无需输入参数。

buy_credits

Buy a credit pack (returns a checkout link)

Get a Stripe checkout link for a one-time credit pack, to hand to the user. Packs: `starter` $9 for 500 credits, `growth` $29 for 2,000 credits, `scale` $99 for 10,000 credits. Credits never expire; 1 credit per document. If this server has an API key set, the credits land on that key's account. Without a key, pass the user's `email` (ask them; do not invent one) — the page after payment shows their new API key. Creating the link charges nothing; the user pays on Stripe's page.

输入参数packemail