Cross-LLM MCP Server

Server Quality Checklist

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Latest release: v1.0.0
Disambiguation5/5
Each tool has a clearly distinct purpose targeting specific resources and actions in the Bitcoin/Lightning domain. For example, decode_invoice and pay_invoice handle Lightning payments, while decode_tx and get_transaction handle Bitcoin transactions, with no overlapping functionality that would cause confusion.
Naming Consistency5/5
All tool names follow a consistent verb_noun pattern using snake_case, such as decode_invoice, generate_key, and validate_address. This uniformity makes the tool set predictable and easy to understand for agents.
Tool Count5/5
With 7 tools, the server is well-scoped for its purpose of Bitcoin and Lightning operations. Each tool serves a specific, necessary function without redundancy, making the count appropriate for the domain's core needs.
Completeness4/5
The tool set covers key operations like decoding, generating, validating, and paying, but there are minor gaps such as creating invoices or managing wallet balances. However, agents can still perform essential workflows with the provided tools.
Average 3/5 across 7 of 7 tools scored.
See the Tool Scores section below for per-tool breakdowns.
- No community issues in the last 6 months
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- No critical vulnerability alerts
- No high-severity vulnerability alerts
- No code scanning findings
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This repository is licensed under MIT License.
This repository includes a README.md file.
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How is the quality score calculated?

The overall quality score combines two components: Tool Definition Quality (70%) and Server Coherence (30%).

Tool Definition Quality measures how well each tool describes itself to AI agents. Every tool is scored 1–5 across six dimensions: Purpose Clarity (25%), Usage Guidelines (20%), Behavioral Transparency (20%), Parameter Semantics (15%), Conciseness & Structure (10%), and Contextual Completeness (10%). The server-level definition quality score is calculated as 60% mean TDQS + 40% minimum TDQS, so a single poorly described tool pulls the score down.

Server Coherence evaluates how well the tools work together as a set, scoring four dimensions equally: Disambiguation (can agents tell tools apart?), Naming Consistency, Tool Count Appropriateness, and Completeness (are there gaps in the tool surface?).

Tiers are derived from the overall score: A (≥3.5), B (≥3.0), C (≥2.0), D (≥1.0), F (<1.0). B and above is considered passing.

Tool Scores

Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. 'Get transaction details' implies a read-only operation, but it doesn't specify whether this requires authentication, has rate limits, returns structured data, or handles errors. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.
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 extremely concise at three words, with zero wasted language. It's front-loaded with the core action ('Get transaction details'), making it easy to scan. Every word earns its place by conveying the essential purpose.
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 the lack of annotations and output schema, the description is incomplete. It doesn't address what details are returned (e.g., amount, timestamp, confirmations), error conditions, or how it differs from sibling tools. For a tool that likely returns complex transaction data, this minimal description leaves too much undefined.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'txid' parameter clearly documented as 'Transaction ID'. The description adds no additional meaning beyond this, as it doesn't explain parameter formats, constraints, or examples. With high schema coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose3/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description 'Get transaction details' clearly states the verb ('Get') and resource ('transaction details'), making the basic purpose understandable. However, it lacks specificity about what details are retrieved and doesn't differentiate from sibling tools like 'decode_tx' or 'get_latest_block', which also involve transaction-related operations.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a transaction ID), exclusions, or comparisons to siblings like 'decode_tx' (which might decode raw transaction data) or 'get_latest_block' (which retrieves block-level information).
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral disclosure. It states the action ('decode') but doesn't explain what the decoding entails - whether it returns structured data like amount, destination, expiry, or just validation status. It also doesn't mention error conditions, rate limits, or authentication requirements, leaving significant gaps in understanding the tool's behavior.
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 extremely concise - a single sentence that directly states the tool's function without any unnecessary words. It's front-loaded with the core purpose and wastes no space on 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?
For a tool with no annotations and no output schema, the description is insufficiently complete. It doesn't explain what the decoding operation returns, what format the output takes, or what information can be extracted from the invoice. Given the complexity of Lightning invoices and the lack of structured output documentation, more context about the decoding results is needed.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% with the single parameter 'invoice' well-documented as 'BOLT11 Lightning invoice'. The description adds no additional parameter semantics beyond what the schema provides, but since the schema does the heavy lifting with complete coverage, the baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('decode') and resource ('a Lightning invoice'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its sibling 'decode_tx' which might handle similar decoding operations for different data types, nor does it specify what kind of information the decoding reveals.
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?
The description provides no guidance on when to use this tool versus alternatives. With siblings like 'decode_tx' (decode transaction) and 'pay_invoice', there's no indication whether this tool should be used for analysis before payment, for validation, or for extracting payment details. No context about prerequisites or exclusions is mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure but only states the action without detailing traits. It doesn't mention whether this is read-only (likely, but not confirmed), if it requires network access, error handling (e.g., for invalid hex), or output format (since no output schema exists). This is a significant gap for a tool with potential complexity.
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, direct sentence with zero wasted words. It front-loads the core action ('Decode a Bitcoin transaction'), making it immediately scannable and efficient. Every word earns its place, adhering to best practices for conciseness.
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 the complexity of Bitcoin transactions and the lack of annotations and output schema, the description is incomplete. It doesn't explain what 'decode' returns (e.g., structured data vs. raw details), error conditions, or dependencies. For a tool that could involve cryptographic parsing, more context is needed to guide the agent effectively.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema description coverage is 100%, with the parameter 'rawHex' clearly documented as 'Transaction hex' in the schema. The description adds no additional meaning beyond this, such as format constraints (e.g., hex string length) or examples. Given the high schema coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but doesn't detract either.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('decode') and resource ('a Bitcoin transaction'), making the purpose immediately understandable. It distinguishes from siblings like 'get_transaction' (which likely retrieves rather than decodes) and 'decode_invoice' (which decodes a different resource). However, it doesn't specify what decoding entails (e.g., extracting inputs/outputs vs. full parsing), keeping it from a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing raw hex data), contrast with 'get_transaction' (which might fetch from a network), or specify use cases (e.g., for analysis vs. validation). This leaves the agent to infer usage from the name alone.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden for behavioral disclosure but offers minimal information. It states 'Pay a Lightning invoice' but doesn't clarify critical traits: whether this is a destructive/mutative operation (likely yes, but not stated), authentication requirements, rate limits, error conditions, or what happens upon success (e.g., funds deducted, invoice marked paid). This leaves significant gaps for an agent to understand the tool's behavior.
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, clear sentence with zero wasted words. It is appropriately sized for a simple tool with one parameter and is front-loaded with the core action. Every part of the sentence earns its place by directly stating the tool's purpose.
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 the complexity (a payment operation likely involving financial transactions), lack of annotations, and no output schema, the description is incomplete. It doesn't address key contextual aspects: what the tool returns (e.g., payment status, transaction ID), error handling, security implications, or dependencies. For a tool that could have significant side effects, this minimal description is insufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% description coverage, with the 'invoice' parameter documented as 'BOLT11 Lightning invoice'. The description adds no additional parameter semantics beyond this, as it doesn't explain format details, validation, or examples. According to scoring rules, with high schema coverage (>80%), the baseline is 3 even without param info in the description.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action ('Pay') and the resource ('a Lightning invoice'), making the purpose immediately understandable. It distinguishes from siblings like decode_invoice or validate_address by specifying a payment action rather than analysis/validation. However, it doesn't specify what 'pay' entails operationally (e.g., sending funds, marking as paid), keeping it from a perfect score.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., needing a funded wallet), exclusions (e.g., not for on-chain payments), or comparisons to sibling tools like decode_invoice (which might be used first to inspect an invoice). Usage is implied only by the tool name and purpose.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe how validation works, what criteria are used, error handling, or output format. For a validation tool with zero annotation coverage, this is a significant gap in transparency.
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, efficient sentence with zero waste. It's appropriately sized for a simple tool and front-loaded with the core purpose, making it easy to parse quickly.
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 the lack of annotations and output schema, the description is incomplete. It doesn't explain what validation entails, what the return values are, or any behavioral traits. For a tool that likely returns a boolean or error message, this leaves critical gaps for an AI agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, with the parameter 'address' fully documented in the schema. The description adds no additional meaning beyond what the schema provides, such as address format examples or validation rules, so it meets the baseline for high schema coverage.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('validate') and resource ('Bitcoin address'), making the purpose immediately understandable. It doesn't differentiate from sibling tools like 'decode_invoice' or 'get_transaction', but the purpose is specific enough to stand alone.
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 doesn't mention prerequisites, context for validation, or how it differs from sibling tools like 'decode_tx' or 'pay_invoice', leaving the agent to infer usage scenarios.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It states a read operation ('Get') but doesn't disclose behavioral traits like whether this is a network call, if it returns cached or real-time data, error conditions, or response format. For a tool with zero annotation coverage, this leaves significant gaps in understanding how it behaves.
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, efficient sentence with zero waste. It's front-loaded with the core action and resource, making it easy to parse. For a simple tool, this minimal structure is appropriate and earns full marks for conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness3/5
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's simplicity (0 parameters, no output schema, no annotations), the description is minimally adequate but incomplete. It lacks context on what 'latest block' means (e.g., blockchain context), return format, or error handling. With no annotations or output schema, the description should provide more behavioral context to be fully helpful.
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 0 parameters, and schema description coverage is 100% (empty schema). The description doesn't need to explain parameters, and it correctly implies no inputs are required. This meets the baseline for parameterless tools, though it could note the absence of parameters more explicitly.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose4/5
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the verb ('Get') and resource ('latest block'), making the purpose immediately understandable. It doesn't distinguish from sibling tools like 'get_transaction', but for a simple read operation with no parameters, this is adequate. The description avoids tautology by specifying 'latest' rather than just restating the name.
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?
The description provides no guidance on when to use this tool versus alternatives like 'get_transaction' or other siblings. It doesn't mention context, prerequisites, or exclusions. The agent must infer usage from the name alone, which is insufficient for optimal tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Behavior2/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden but only states the basic action. It doesn't disclose behavioral traits like whether this is a read-only operation, if it requires network access, potential security implications, or what format the output takes. This is inadequate for a tool that generates cryptographic keys.
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, efficient sentence with zero wasted words. It is front-loaded with the core action and resource, making it immediately understandable without unnecessary elaboration.
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 the complexity of generating cryptographic keys and the lack of annotations or output schema, the description is insufficient. It doesn't explain the output format, security considerations, or potential side effects, leaving critical gaps for an agent to use this tool effectively.
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 0 parameters with 100% schema coverage, so no parameter documentation is needed. The description appropriately focuses on the tool's purpose without redundant parameter details, meeting the baseline for parameterless tools.
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 specific action ('generate') and the exact resource ('a new Bitcoin key pair and address'), distinguishing it from siblings like decode_invoice or validate_address. It uses precise terminology that leaves no ambiguity about what the tool produces.
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?
The description provides no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, typical use cases (e.g., for new wallets), or contrast with sibling tools like get_transaction or pay_invoice, leaving the agent to infer context independently.
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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