AIDataParser
REMOTE · AIDATAPARSER.COM · SCANNED OCT 4
PDFs, images and messy text to schema-guaranteed JSON. try_parse runs a real extraction, no key.
Available components
How this component scores in each security and reliability category. Every signal is checked automatically against the live server, and we only credit what we can confirm. How we score → Why this is hard to score →
Endpoint Security80
- The endpoint's TLS certificate is valid, in date, and uses a strong key. View diagnostics → Pass
- No authorisation is required to call this server. Every tool declares its destructiveHint and none is destructive, so open access doesn't expose one. See how to fix → View diagnostics → Partial
- HTTPS is enforced; there's no plaintext access path. View diagnostics → Pass
- The HSTS (Strict-Transport-Security) header is present. View diagnostics → Pass
- DNSSEC check failed: this domain isn't protected by DNSSEC. See how to fix → View diagnostics → Fail
Transport & Reachability100
- Verified streamable-http transport via a live MCP handshake. View diagnostics → Pass
Schema Quality & AI Usability72
- AI-judged instruction clarity (excellent).Pass
- Context-footprint check failed: tool/resource definitions use about 1544 tokens (~193/item across 8 items; 8 tools + 0 resources), over budget; trim descriptions and params. See how to fix → Fail
- Usage-examples check failed: none of the tools include examples. See how to fix → Fail
Stability & Change Management40
- Stability observed for 12 of 30 days with no destabilising changes; credit accrues until the full window elapses.Partial
Tool Coverage100
- 100% of tools have a non-trivial description (not blank, and not just the tool's name).Pass
- 100% of tool parameters carry a description.Pass
Tool Safety100
- No prompt-injection markers were found in the server instructions, tool names or descriptions we captured.Pass
- We read all 8 captured tool definition(s), and no name or description among them implies an irreversible operation.Pass
- An AI judge read all 9 captured unit(s) of tool text and found none that tries to manipulate the model reading it.Pass
Capabilities60
- Spec-recency check failed: implements MCP spec 2025-06-18; the latest is 2026-07-28. See how to fix → Fail
How do I install the AIDataParser MCP server?
AIDataParser is a hosted endpoint at https://aidataparser.com/v1/mcp, so there is nothing to install locally. Ready-made configuration for Claude, Cursor, VS Code, Codex and 5 more is on this page, copied from each client's own documentation.
remote · aidataparser.com
claude mcp add --transport http shibley-aidataparser 'https://aidataparser.com/v1/mcp'
{
"mcpServers": {
"shibley-aidataparser": {
"url": "https://aidataparser.com/v1/mcp"
}
}
} {
"servers": {
"shibley-aidataparser": {
"type": "http",
"url": "https://aidataparser.com/v1/mcp"
}
}
} [mcp_servers.shibley-aidataparser] url = "https://aidataparser.com/v1/mcp"
{
"$schema": "https://opencode.ai/config.json",
"mcp": {
"shibley-aidataparser": {
"type": "remote",
"url": "https://aidataparser.com/v1/mcp",
"enabled": true
}
}
} openclaw mcp add shibley-aidataparser --url 'https://aidataparser.com/v1/mcp' --transport streamable-http
mcp_servers:
shibley-aidataparser:
url: "https://aidataparser.com/v1/mcp" {
"McpServers": {
"shibley-aidataparser": {
"Transport": "http",
"Url": "https://aidataparser.com/v1/mcp"
}
}
} assistant mcp add shibley-aidataparser -t streamable-http -u 'https://aidataparser.com/v1/mcp'
{
"mcpServers": {
"shibley-aidataparser": {
"type": "http",
"url": "https://aidataparser.com/v1/mcp"
}
}
} The mcpServers block is a cross-client convention. Remote transports vary, so check your client's docs.
Every change we have recorded for this component, newest first. Security-relevant changes are always shown. ▲ marks a change for the better, ▼ a change for the worse; unmarked changes are neutral.
- 3 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 33 to 37. That category is still filling its 30-day observation window: 10 days of observed history at the previous scan, 11 at this one. The score rises as the window fills, whether or not the server changes.
- 1 Oct 26 +1
No change was recorded against any check on this day. Stability & Change Management went from 27 to 30. That category is still filling its 30-day observation window: 8 days of observed history at the previous scan, 9 at this one. The score rises as the window fills, whether or not the server changes.
- 30 Sept 26 0
- The server rewrote its instructions, which are the text every model session reads security
- Schema quality: 1239 → 1544 ▼ functional
- New tool “try_parse” functional
- 28 Sept 26 +1
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 27 Sept 26 +7
- Authorization: unverified → partial ▲ security
- 25 Sept 26 +1
- We updated how we score, so this day's move reflects our rubric, not a change to the server See what changed → functional
- 23 Sept 26 +1
- Stability: unverified → 0.03 ▲ functional
- 22 Sept 26 65
First indexed and scored.
Diagnostic detail from the automated scan of this channel: what the scanner observed at each step, so you can see exactly where a check passed or failed. It is informational only and never changes the trust score.
Captured 4 Oct 2026 · Probed https://aidataparser.com/v1/mcp
TLS valid
Negotiated TLS 1.3 with TLS_AES_128_GCM_SHA256 .
| Subject | Issuer | Valid from | Valid until | Key | Signature | Serial |
|---|---|---|---|---|---|---|
| CN=aidataparser.com | CN=YR1,O=Let's Encrypt,C=US | 11 Sept 2026 | 10 Dec 2026 | RSA 2048 | SHA256-RSA | 6b42b06b464d50e4b26db62483c36fa95c8 |
| SANs: aidataparser.com, www.aidataparser.com | ||||||
| CN=YR1,O=Let's Encrypt,C=US (CA) | CN=Root YR,O=ISRG,C=US | 3 Sept 2025 | 2 Sept 2028 | RSA 2048 | SHA256-RSA | a20253f15f2691c05dc1ce13b9bcca4e |
| CN=Root YR,O=ISRG,C=US (CA) | CN=ISRG Root X1,O=Internet Security Research Group,C=US | 13 May 2026 | 2 Sept 2032 | RSA 4096 | SHA256-RSA | f24b6d17f9d9ad7cb1c9fea78782699f |
Background: What to check on a remote MCP endpoint →
DNSSEC insecure
Validation of aidataparser.com. — Not signed
| Zone | DS | Keys | Algorithms | Outcome |
|---|---|---|---|---|
| . | trust_anchor | 20326, 38696 | 8, 8 | Verified |
| com. | present | 19718 | 13 | Verified |
| aidataparser.com. | absent | Unsigned (proven) parent-signed NSEC/NSEC3 proves an unsigned delegation |
Authentication No authorisation required
The endpoint answered without asking for a token. Anyone who knows the URL can reach it.
| Result | No authorisation required |
|---|---|
| HTTP status | 200 |
| Header | Value |
|---|---|
| strict-transport-security | max-age=63072000 |
Background: How OAuth 2.1 works in the 2026 MCP spec →
Transports 2 probes
| Transport | URL | Outcome | Status | Location |
|---|---|---|---|---|
| streamable-http | https://aidataparser.com/v1/mcp | Verified | 200 | |
| http (plaintext) | http://aidataparser.com/v1/mcp | HTTPS enforced | 308 | https://aidataparser.com/v1/mcp |
The tools this component advertises to a client, with an estimated token cost for each. Expand a tool to see its parameters and schema. The per-tool counts are indicative and are not scored directly; the schema's total context footprint is one signal in Schema Quality & AI Usability. A tool's description is untrusted text the model reads on every call, which is what makes this list a security surface and not just an inventory: how tool poisoning works →
check_credits Check remaining credits ~30
Return the number of extraction credits remaining on the authenticated API key. Free — does not consume a credit.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
create_api_key Get an API key with free credits ~159
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.
| Name | Type | Req | Description |
|---|---|---|---|
| string | yes | The user's email address. The account and its free credits belong to this address; an address that already has an account is refused rather than issued a second key. |
No output schema declared.
No examples provided.
infer_schema Infer a reusable JSON Schema from a sample ~152
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.
| Name | Type | Req | Description |
|---|---|---|---|
| doc_type | string | – | Optional hint for what kind of document this is, e.g. "purchase order", "lab report". |
| instructions | string | – | Optional guidance on which fields matter or how to shape the schema. |
| text | string | yes | A single representative sample of the document type, as text. |
No output schema declared.
No examples provided.
list_schemas List built-in schema templates ~58
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.
Input schema present but exposes no named parameters.
No output schema declared.
No examples provided.
parse_document Parse a document into structured JSON ~281
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.
| Name | Type | Req | Description |
|---|---|---|---|
| base64 | string | – | Base64-encoded document bytes (alternative to `url`). Provide `media_type` alongside it. |
| instructions | string | – | Optional natural-language guidance for what to extract. |
| media_type | string | – | MIME type for `base64` input, e.g. application/pdf, image/png, image/jpeg. |
| redact | boolean | – | When true, PII (emails, SSNs, card numbers, phones, etc.) is masked in the output before it leaves the server. |
| schema | object | – | Optional JSON Schema describing the exact output shape you want. When provided, the returned `data` conforms to it. |
| schema_id | string | – | Optional named template to use instead of a hand-written schema, e.g. "invoice", "receipt", "resume". Call the list_schemas tool for the full set. Ignored when `schema` is provided. |
| url | string | – | Public http(s) URL of the PDF or image to parse. |
No output schema declared.
No examples provided.
parse_text Parse raw text into structured JSON ~253
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.
| Name | Type | Req | Description |
|---|---|---|---|
| instructions | string | – | Optional natural-language guidance for what to extract. |
| redact | boolean | – | When true, PII (emails, SSNs, card numbers, phones, etc.) is masked in the output before it leaves the server. |
| schema | object | – | Optional JSON Schema describing the exact output shape you want. When provided, the returned `data` conforms to it. |
| schema_id | string | – | Optional named template to use instead of a hand-written schema, e.g. "invoice", "receipt", "resume". Call the list_schemas tool for the full set. Ignored when `schema` is provided. |
| text | string | yes | The raw text to extract structured data from. |
No output schema declared.
No examples provided.
try_parse Try it now — parse text into JSON with no API key ~254
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.
| Name | Type | Req | Description |
|---|---|---|---|
| instructions | string | – | Optional natural-language guidance for what to extract. |
| schema | object | – | Optional JSON Schema describing the exact output shape you want. When provided, the returned `data` conforms to it. |
| schema_id | string | – | Optional named template to use instead of a hand-written schema, e.g. "invoice", "receipt", "resume". Call list_schemas for the full set. Ignored when `schema` is provided. |
| text | string | yes | The raw text to extract structured data from, up to 4000 characters. Send a representative excerpt rather than a whole corpus. |
No output schema declared.
No examples provided.
validate Validate JSON against a schema ~151
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.
| Name | Type | Req | Description |
|---|---|---|---|
| data | – | yes | The JSON value to validate. |
| schema | object | – | JSON Schema to validate against. Takes precedence over schema_id. |
| schema_id | string | – | Built-in template id to validate against instead of a hand-written schema (invoice, receipt, resume, etc.). Call list_schemas for the full set. |
No output schema declared.
No examples provided.
What is the AIDataParser MCP server?
AIDataParser is an MCP server listed in the public MCP registry as io.github.shibley/aidataparser. PDFs, images and messy text to schema-guaranteed JSON. try_parse runs a real extraction, no key. This page covers its hosted endpoint (https://aidataparser.com/v1/mcp).
Is the AIDataParser MCP server safe to use?
AIDataParser scores 77 out of 100 on VerifyMCP. That is a record of what we were able to check automatically, not an endorsement. The category breakdown on this page shows every signal behind the number, including the ones we could not confirm.
What tools does the AIDataParser MCP server expose?
AIDataParser exposes 8 tools: try_parse, create_api_key, parse_document, parse_text, infer_schema, and 3 more. Their descriptions and schemas cost roughly 1,338 tokens of context every time the server is loaded.
Does the AIDataParser MCP server require authentication?
No. We connected to AIDataParser without credentials and it answered, so anything it exposes is reachable by anyone who knows the address.
Is the AIDataParser MCP server still maintained?
AIDataParser is still listed as active in the MCP registry. We last reached this channel on 4 October 2026. Those dates come from our own scans of the registry and the channel itself, not from anything the publisher announced.