A
license-
qualityD
maintenanceMCP server for ReceiptConverter that allows AI assistants to parse any receipt or invoice image/PDF into structured JSON with a single tool call.
7
MIT
AskAIs AI Receipt Generator
Server Details
Generate professional receipt PDFs and structured receipt data with AI-ready MCP tools.
- Status
- Healthy
- Last Tested
- Transport
- Streamable HTTP
- URL
- Repository
- MiniCodeTeam/askais-mcp
- GitHub Stars
- 1
- Server Listing
- AskAIs AI Receipt Generator MCP
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MCP client
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MCP server
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Usage analytics
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100% free. Your data is private.
Tool Definition Quality
A3.9/5.0
Tool DescriptionsA
Average 3.7/5 across 4 of 4 tools scored. Lowest: 3.1/5.
Server CoherenceA
Disambiguation5/5
Each tool has a clear, distinct purpose: account creation, receipt generation, balance checking, and rules reading. There is no overlap or ambiguity.
Naming Consistency5/5
All tools follow a consistent verb_noun pattern in snake_case: create_free_account, generate_receipt, get_balance, get_usage_rules.
Tool Count5/5
With 4 tools, the set is appropriately scoped for a receipt generation service, covering account management, generation, balance, and rules.
Completeness4/5
The core workflow is covered (account, generation, balance, rules), but missing features like viewing past receipts or deleting accounts are minor gaps.
Available Tools
4 toolscreate_free_accountCreate a free AskAIs accountAInspect
Create an AskAIs account without opening a browser. Returns one-time login credentials and an API key with introductory receipt credit. The user must explicitly accept the Terms and Privacy Policy.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| client_name | No | MCP host name, for example Cursor, Claude Code, Codex, or Gemini CLI. | |
| accept_terms | Yes | Must be true after the user agrees to AskAIs Terms and Privacy Policy. | |
| client_version | No | ||
| preferred_language | No |
Tool Definition Quality
A3.5/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of behavioral disclosure. It mentions return values and the requirement to accept terms, but lacks details on error handling, idempotency, or potential state changes. More context would be beneficial.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Three concise, front-loaded sentences that quickly convey purpose, return value, and requirement. No extraneous information; every sentence adds value.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Covers core purpose, return items, and acceptance requirement. However, it omits details about the 'introductory receipt credit' and the one-time nature of credentials. With no output schema, a more structured description of the return format would improve completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters2/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 50%, and the description adds no additional meaning for any parameter. Two parameters (client_version, preferred_language) remain undefined, and no extra context is provided beyond the schema's descriptions for client_name and accept_terms.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Create' and the resource 'AskAIs account', and provides additional context about browserless creation and return values. It distinguishes itself from sibling tools focused on receipts and balance management.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines2/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No guidance is provided on when to use this tool versus alternatives. The description does not mention scenarios, prerequisites, or exclusions, leaving the agent to infer use cases from the sibling context.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
generate_receiptGenerate a professional receipt PDFBInspect
Generate a downloadable receipt PDF for a legitimate transaction. Costs $0.10 only on successful generation.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| date | No | Receipt date, preferably YYYY-MM-DD. | |
| items | No | ||
| notes | No | ||
| api_key | No | Optional after create_free_account succeeds in this MCP session. | |
| currency | No | Currency symbol or code, for example USD, HKD, or $. | |
| language | No | ||
| text_color | No | ||
| total_amount | No | ||
| customer_name | Yes | ||
| primary_color | No | ||
| contact_person | No | ||
| customer_email | No | ||
| customer_notes | No | ||
| customer_phone | No | ||
| invoice_number | No | ||
| payment_method | No | ||
| customer_address | No | ||
| customer_registration_number | No | ||
| confirm_legitimate_transaction | Yes | Must be true. Confirms this receipt represents a legitimate transaction and will not be used to deceive. |
Tool Definition Quality
B3.1/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description must cover behavioral traits. It mentions cost ($0.10 on success) but omits idempotency, state changes, authentication needs, or failure behavior. Insufficient for a tool with financial implications.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Extremely concise with two sentences, front-loaded with purpose and cost. No redundant information.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness2/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given 19 parameters, no output schema, and required confirm_legitimate_transaction, the description lacks critical context such as output format, how to retrieve the PDF, or how items array works. Incomplete for reliable invocation.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters1/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is low (21%), so description should compensate, but it adds no parameter semantics. The description does not explain any of the 19 parameters beyond what the schema provides.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states it generates a downloadable receipt PDF for a legitimate transaction, uses a specific verb and resource, and the cost is mentioned, distinguishing it from sibling tools like create_free_account.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool vs alternatives. The api_key parameter description notes optionality after account creation, but overall lacks contextual usage direction.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_balanceGet AskAIs API balanceAInspect
Return the remaining prepaid AskAIs API credit for the connected account.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
| api_key | No | Optional after create_free_account succeeds in this MCP session. |
Tool Definition Quality
A3.8/5.0
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations exist, so description carries full burden. It does not disclose whether the call consumes credit, requires authentication, or handles missing accounts. Minimal behavioral context beyond the basic operation.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
Single sentence, no wasted words, immediately clear.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with one optional parameter and no output schema, the description adequately explains what is returned and for which account. Could mention return format but not necessary.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Description adds value over the schema by noting the api_key parameter is 'Optional after create_free_account succeeds'. Schema coverage is 100% but description provides practical context.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb 'Return' and the resource 'remaining prepaid AskAIs API credit', and differentiates from siblings like create_free_account and generate_receipt.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit guidance on when to use this tool versus alternatives (e.g., after account creation or before API calls). The purpose is implied but not stated.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_usage_rulesGet AskAIs usage rulesAInspect
Read pricing, free-credit, privacy, and acceptable-use rules before creating an account or receipt.
ParametersJSON Schema
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
Tool Definition Quality
A4.3/5.0
Behavior3/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It indicates a read-only operation (non-destructive) but lacks details on data freshness, authentication needs, or any potential side effects. The behavior is straightforward, so a score of 3 is appropriate.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is a single sentence of 14 words, front-loading the action 'Read'. Every word is essential, and no redundant information is present.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
With no parameters, no output schema, and simple read behavior, the description fully covers the necessary context: what the tool does and when to use it. No additional information is required for an AI to select and invoke this tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters with 100% schema coverage, so baseline is 4. The description adds value by specifying the content of the rules (pricing, free-credit, privacy, acceptable-use), compensating for the lack of parameters.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action 'Read' and the resource 'pricing, free-credit, privacy, and acceptable-use rules'. It distinguishes itself from siblings (create_free_account, generate_receipt, get_balance) by specifying the purpose of reading rules before other actions.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly advises using this tool 'before creating an account or receipt', providing clear context. It does not mention alternatives directly, but the sibling tools are distinct in function, making the usage context unambiguous.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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