Skip to main content
Glama
cmdenney

@logicnodez/mcp-bridge

by cmdenney

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v1.0.4

  • Disambiguation5/5

    Each tool targets a distinct blockchain operation: signature verification, gas oracle, peg monitoring, escrow verification, identity registration, inference attestation, compliance checking, and ZK compute attestation. No overlapping purposes.

    Naming Consistency5/5

    All tools follow the consistent pattern 'logicnodes_<descriptive_snake_case_name>' (e.g., sig_verify, gas_oracle, zk_compute_attest). The naming is predictable and clear.

    Tool Count5/5

    8 tools is an appropriate count for a blockchain bridge server. It covers a breadth of functionalities without being overwhelming or too sparse.

    Completeness4/5

    The tool surface covers core bridge operations (verification, monitoring, registration, attestation). A minor gap is a generic transaction or balance checking tool, but the set is largely complete for its domain.

  • Average 3.7/5 across 8 of 8 tools scored. Lowest: 2.9/5.

    See the Tool Scores section below for per-tool breakdowns.

    • 0 of 1 community issues answered or closed in the last 6 months
    • 14 commits in the last 12 weeks
    • No stable releases found
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI is passing
  • This repository is licensed under MIT License.

  • This repository includes a README.md file.

  • No tool usage detected in the last 30 days. Usage tracking helps demonstrate server value.

    Tip: use the "Try in Browser" feature on the server page to seed initial usage.

  • Add a glama.json file to provide metadata about your server.

  • If you are the author, simply .

    If the server belongs to an organization, first add glama.json to the root of your repository:

    {
      "$schema": "https://glama.ai/mcp/schemas/server.json",
      "maintainers": [
        "your-github-username"
      ]
    }

    Then . Browse examples.

  • Add related servers to improve discoverability.

How to sync the server with GitHub?

Servers are automatically synced at least once per day, but you can also sync manually at any time to instantly update the server profile.

To manually sync the server, click the "Sync Server" button in the MCP server admin interface.

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?

    Discloses cost ($0.001 USDC) and mentions the receipt, but lacks details on side effects, permissions, or error scenarios. No annotations provided, so description carries full burden but is insufficient.

    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?

    Two concise sentences, front-loaded with verb, no redundant information. Every word adds value.

    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?

    Without output schema or annotations, the description should provide more context on usage, return values, and error handling. It is incomplete for a tool with 4 parameters.

    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 covers 75% of parameters with descriptions. Description adds no additional parameter information beyond what is in the input schema, so baseline 3 applies.

    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?

    Description clearly states the tool attests an AI inference result on-chain and produces a signed POL receipt. It specifies the platform and output, but does not explicitly distinguish from sibling tools like zk_compute_attest.

    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 on when to use this tool versus alternatives. The description does not indicate prerequisites, exclusions, or context for usage.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations provided, the description carries the full burden. It discloses the cost ($0.0001 USDC per call) and mentions returning the signer address with on-chain proof, but it does not explicitly state whether the tool is read-only, requires authentication, or has rate limits. Since it's a verification tool, it is likely non-destructive, but this is not confirmed.

    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 two sentences: one clearly stating functionality and one specifying cost. It is concise, front-loaded with the core purpose, and contains no unnecessary words.

    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 has no output schema and only medium parameter count, the description covers the basic purpose and cost. However, it lacks details on input format requirements (e.g., encoding of message and signature), expected return structure (e.g., address format), and any prerequisites. For a developer to use this tool confidently, more detail would be beneficial.

    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 only 33% (only expected_signer has a description). The tool description adds context by stating it verifies EIP-712 typed data signatures, implying that 'message' is the typed data and 'signature' is the cryptographic signature. However, it does not explicitly define these parameters' formats (e.g., hex, JSON) or provide per-parameter guidance, leaving ambiguity.

    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 tool performs cryptographic signature verification on Base, specifically EIP-712 typed data, and returns the signer address with on-chain proof. The verb 'verifies' and resource 'signatures' are specific, and the scope (Base blockchain, EIP-712) distinguishes it from sibling tools like logicnodes_gas_oracle or logicnodes_peg_monitor.

    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?

    The description implies usage for verifying EIP-712 typed data signatures on Base, but it provides no explicit guidance on when to use this tool versus alternatives, nor does it specify conditions for use or exclusions. The cost mention is helpful but not sufficient for clear usage guidelines.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description must disclose behavioral traits. It reveals return type (ZK proof hash), anchoring, and cost per proof. However, it does not address idempotency, side effects, authorization, or state mutation, leaving gaps.

    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 three concise sentences, each adding unique value: purpose, proof property, and output with cost. No unnecessary words; front-loaded with core functionality.

    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 no output schema or annotations, the description explains purpose and return type, but omits usage guidelines, detailed parameter roles, behavioral details, and full output format. Adequate but not comprehensive.

    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 67%, but the tool description adds no per-parameter explanation beyond schema. public_inputs lacks description in both schema and tool description, leaving its role unclear.

    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 tool performs zero-knowledge compute attestation, proving computation correctness without revealing inputs. It distinguishes from siblings by specifying ZK and anchoring to Base, and mentions returning a proof hash and cost.

    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?

    The description implies use for verifying computations with ZK, but does not explicitly state when to use this tool vs alternatives like logicnodes_inference_attest or logicnodes_sig_verify. No exclusion criteria or prerequisites are mentioned.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description must disclose behavior. It mentions it is 'autonomous', checks against rules, returns attestation hash and compliance score, and discloses cost ($0.01 USDC). However, it does not clarify if it is read-only or creates records, nor what happens on non-compliance.

    Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

    Conciseness4/5

    Is the description appropriately sized, front-loaded, and free of redundancy?

    The description is very concise, with four short statements that front-load the main purpose. It wastes no words, though it could be slightly more structured (e.g., bullet points).

    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?

    Given the absence of an output schema, the description adequately explains what is returned (attestation hash and compliance score). It lists the regulations checked and the cost. However, it lacks details on error handling or prerequisites, but overall is sufficiently complete for a simple compliance check tool.

    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% (all three parameters have descriptions). The tool description does not add any additional meaning beyond what the schema already provides, so baseline 3 is appropriate.

    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 tool performs 'regulatory attestation' and 'checks action against MiCA, EU AI Act, and US EO compliance rules', with specific verb 'Checks' and resource 'compliance rules'. It distinguishes from siblings like logicnodes_sig_verify and logicnodes_gas_oracle which serve different purposes.

    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?

    The description implies it is used for agent transactions needing compliance checks, mentioning cost per check, but does not explicitly state when to use it versus alternatives (e.g., inference_attest) or when not to use it (e.g., if no regulatory jurisdiction applies).

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description carries the full burden. It discloses cost and return values, but does not cover failure modes, idempotency, or permission requirements. Adequate but not exhaustive.

    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 two sentences, front-loaded with the primary action, and includes essential details (cost) without any fluff.

    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 complexity and full schema coverage, the description covers purpose, return, and cost, but lacks context on prerequisites, error handling, or when this tool should be chosen over siblings.

    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, so the baseline is 3. The description adds no extra meaning to parameters beyond what the schema already 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 the verb 'register' and the specific resource 'agent identity on Base mainnet via AgentIdentityRoot'. It also mentions return values and cost, making it distinct from sibling tools which are verification, oracle, monitoring, etc.

    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?

    The description implies use for registering identities, but lacks explicit guidance on when not to use it or alternatives. No prerequisites or success/failure conditions are 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, the description should disclose behavioral traits. It mentions cost and outputs but does not state that it is read-only, any side effects, authorization needs, or rate limits.

    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?

    Two sentences, front-loaded with purpose, then outputs and cost. Every sentence earns its place with no fluff.

    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?

    For a simple tool with one optional parameter and no output schema, the description explains what it returns but lacks detail on output format and the effect of threshold_bps. Adequate but could be more complete.

    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 coverage is 100% and the parameter description in schema is sufficient. The tool description does not add additional meaning 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 is a 'USDC peg stability monitor' and lists specific outputs: deviation, reserve attestation, risk score. It distinguishes itself from unrelated sibling tools.

    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 implies usage for USDC peg status without explicit alternatives or exclusions. The cost note provides practical guidance, but no 'when not to use' is stated.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior3/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    No annotations are provided, so the description must disclose behavioral traits. It mentions a cost of $0.001 USDC per call, which is useful, but it does not state whether the operation is read-only or whether it involves side effects. The tool name suggests a verifier (likely read-only), but this is not explicit. Missing details about what happens on error or confirmation.

    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?

    Two sentences with no filler. The first states the purpose, the second adds a critical cost detail. Every word earns its place. Very efficient.

    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?

    With no output schema, the description should hint at return values or side effects. It does not mention what the tool returns (e.g., a status, balance value, or boolean). Also, no prerequisites (e.g., network connection, API key) are stated. The cost note is good, but overall completeness is adequate but not thorough.

    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?

    Schema coverage is 100%, so baseline is 3. The description adds value by explaining that the tool checks 'balance and release conditions', giving context to the parameters escrow_id and party_address. This helps the agent understand that the parameters are used to fetch specific escrow details, going beyond the bare schema types.

    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?

    Description clearly states the tool checks the LogicNodesEscrow contract for active escrow, balance, and release conditions. The verb 'checks' and specific resource 'LogicNodesEscrow contract' make purpose unambiguous. Among siblings like logicnodes_sig_verify or logicnodes_gas_oracle, this tool is distinctly about escrow verification.

    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?

    Usage is implied: use when you need to verify on-chain escrow state. However, no explicit when-to-use or when-not-to-use guidance is given, nor are alternatives mentioned despite having 7 sibling tools. The description lacks exclusions or context for distinguishing from other verification tools.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

  • Behavior4/5

    Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

    With no annotations, the description carries the full burden. It discloses the cost per call and real-time nature, which are important behavioral traits. However, it does not explicitly state that the tool is read-only or safe, but the nature of an oracle implies no destructive side effects.

    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: two sentences and a cost line. Every sentence adds value with no redundancy or fluff. The most important information (purpose, outputs) comes first.

    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?

    Given the tool's simplicity (one optional parameter, no output schema, no annotations), the description provides complete context: what data it returns, which network, and the cost. The agent has sufficient information to decide and invoke.

    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% coverage as the sole parameter 'percentile' is fully described. The tool description adds no additional meaning beyond the schema, so the baseline score of 3 applies.

    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 tool is a real-time gas price oracle for Base mainnet, listing specific return values (base fee, priority fee, EIP-1559 deviation). It distinguishes itself from sibling tools like logicnodes_sig_verify and logicnodes_peg_monitor, which serve different purposes.

    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?

    The description implicitly suggests using the tool when needing gas price data, but provides no explicit guidance on when to use it over alternatives or when not to use it. The mention of cost and real-time data gives some context, but lacks direct usage instructions.

    Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

GitHub Badge

Glama performs regular codebase and documentation scans to:

  • Confirm that the MCP server is working as expected.
  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

Our badge communicates server capabilities, safety, and installation instructions.

Card Badge

logicnodes-mcp-bridge MCP server

Copy to your README.md:

Score Badge

logicnodes-mcp-bridge MCP server

Copy to your README.md:

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/cmdenney/logicnodes-mcp-bridge'

If you have feedback or need assistance with the MCP directory API, please join our Discord server