# Shibley Aidataparser MCP server

Source: https://glimind.com/server/mcp-registry%2Fio.github.shibley%2Faidataparser
Registry id: `mcp-registry/io.github.shibley/aidataparser`
Status: live (checked 2026-10-26T20:36:58.431Z)

## Verdict

Shibley Aidataparser MCP server answered 99.97% of Glimind's liveness checks over 30 days, better than 41% of MCP servers, with 736 ms median handshake and 1 outage in 90 days. Its agent-readiness grade is A (93/100) across 9 tools, costing an agent about 2,142 tokens to load. Checked every few minutes; no tool is ever called.

## Measurements (30 days)

| Metric | Value | Better than |
|---|---|---|
| Uptime, 30 days | 99.97% | 41% of MCP servers |
| Median handshake latency | 736 ms | 36% of MCP servers |
| p95 handshake latency | 3383 ms | — |
| Checks in 30 days | 4,905 | — |
| Outages, 90 days | 1 | — |
| Median recovery | 8 min | — |
| Agent-readiness score | 93/100 (A) | 76% of MCP servers |
| Tools | 9 | — |
| Tool-list size for an agent | ~2,142 tokens | 51% of MCP servers |
| Days observed | 29 | — |

## Install

```json
{
  "mcpServers": {
    "shibley-aidataparser-mcp-server": {
      "type": "http",
      "url": "https://aidataparser.com/v1/mcp"
    }
  }
}
```

Claude Code:

```sh
claude mcp add --transport http shibley-aidataparser-mcp-server https://aidataparser.com/v1/mcp
```

## Tools (9)

- `buy_credits`: 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
- `check_credits`: Return the number of extraction credits remaining on the authenticated API key. Free — does not consume a credit.
- `create_api_key`: 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
- `infer_schema`: 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
- `list_schemas`: 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
- `parse_document`: 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 sh
- `parse_text`: 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 th
- `try_parse`: 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 mess
- `validate`: 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

Measured by Glimind (https://glimind.com): MCP handshake + tool list only, no tool is ever called. CC BY 4.0.