AIDataParser

io.github.shibleyPublished by GitHub account shibleyv0.2.0Updated Oct 24, 2026

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

The publisher's own server: Parser Club

VerifiedStreamable HTTPWeb executableFiles & StorageData & Analytics

Overview

AI-generated overview

AIDataParser is a hosted MCP server that turns PDFs, images and messy text into schema-guaranteed JSON, with a free trial extraction and credit-based paid par.

What you can do
Run a free trial extraction on up to 4,000 characters of text to preview the output shape, with no key or account needed, limited to 3 calls per day. Extract schema-constrained JSON from PDFs or images supplied by URL or base64, and from raw or messy text such as scraped pages, emails, chat logs or OCR output. Infer a reusable JSON Schema from one sample document, and list the built-in templates such as invoice, receipt and resume. Validate a JSON object against a schema or built-in template and get per-field errors. Create an API key from an email address, check remaining credits, and get a Stripe checkout link for credit packs.
When to use it
Use it when an assistant needs to convert invoices, receipts, resumes, scanned documents or unstructured text into structured JSON that follows a fixed schema, and when you want to test extraction quality before paying. It suits document-processing and data-entry workflows rather than general file storage or search.
Requirements
A remote Streamable HTTP endpoint; no local runtime or package is needed. The free tools try_parse, list_schemas and validate need no key. Paid tools need an AIDataParser API key, obtained through create_api_key with an email address or the keys endpoint, configured as an Authorization Bearer header. Credits are consumed per document.
Before you install
create_api_key requires the user's email address and returns a live API key; treat that key as a secret. parse_document and parse_text send document contents or text to a third-party service and cost 1 credit each. buy_credits returns a Stripe checkout link for real money, and purchased credits attach to the account of the configured key. Free trial calls are limited to 3 per day.

Installation

In SourceWeft

  1. Open AIDataParser in the dashboard and add it to a workspace.
  2. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/io.github.shibley%2Faidataparser/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "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_..." }    }  }}

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" } }

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]"}'

Tools

ToolCostWhat it does
try_parsefree, no keyReal extraction on ≤4,000 chars of text, 3/day — see the output before signing up
create_api_keyfree, no keyAn email → a live adp_live_ key with 50 free credits
parse_document1 creditPDF or image (url or base64) → JSON matching your schema
parse_text1 creditRaw/messy text → JSON matching your schema
infer_schema1 creditOne sample → a reusable JSON Schema
validatefree, no keyCheck a JSON value against a schema
check_creditsfreeCredits remaining on the key
list_schemasfree, no keyBuilt-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.

Source: README.md at commit 0f4d885

Tools

9

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.

Parameterstextrequiredschemaschema_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.

Parametersemailrequired

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.

Parametersurlbase64redactschemaschema_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.

Parameterstextrequiredredactschemaschema_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.

Parameterstextrequireddoc_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.

Parametersdatarequiredschemaschema_id

check_credits

Check remaining credits

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

Takes no parameters.

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.

Takes no parameters.

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.

Parameterspackemail

Version history

2
  1. v0.2.0LatestOct 1, 2026
  2. v0.1.0Sep 22, 2026

Score

100% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts
  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

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