Skip to main content
Glama
abe-source

mcp-crypto-arbitrage

by abe-source
OverviewSchemaRelated ServersScoreDiscussions
TypeScript

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a clearly distinct purpose: get_coin_prices retrieves prices, find_arbitrage analyzes a single coin's spread, and scan_top_coins scans multiple coins. No overlap.

    Naming Consistency5/5

    All tool names follow a consistent verb_noun pattern in snake_case: get_coin_prices, find_arbitrage, scan_top_coins. Very predictable.

    Tool Count5/5

    Three tools is appropriate for a focused crypto arbitrage server. Each tool adds distinct value without redundancy.

    Completeness4/5

    Covers core arbitrage functionality: price retrieval, single-coin spread, and multi-coin scan. Minor gap: no tool for listing supported coins or exchanges, but CoinGecko IDs are well-known.

  • Average 3.8/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 1 commit in the last 12 weeks
    • Last stable release on
    • No critical vulnerability alerts
    • No high-severity vulnerability alerts
    • No code scanning findings
    • CI status not available

  • 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

  • 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 discloses the main behavior but lacks details on scope (e.g., which exchanges), latency, or behavior when no spread meets the threshold. Adequate but leaves 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?

    A single, clear, and efficient sentence with no wasted words. Front-loaded with the core purpose.

    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 2 parameters and no output schema, the description is minimally adequate. It lacks details on return format or edge cases (e.g., no spread found), but is functional for basic use.

    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% so the baseline is 3. The description adds no new meaning beyond stating the condition 'above a minimum percentage', which is already in the schema's description for min_spread_pct.

    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 'find', the resource 'cross-exchange USD/USDT price spread for one coin', and a condition 'above a minimum percentage'. It distinguishes from siblings: 'get_coin_prices' retrieves prices, 'scan_top_coins' scans multiple coins.

    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 arbitrage detection but does not explicitly state when to use this tool versus alternatives like 'get_coin_prices' or 'scan_top_coins'. No when-not-to-use guidance is provided.

    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 carries full burden. It only states the basic behavior (get prices) without disclosing any side effects, rate limits, data freshness, or potential errors. For a simple read operation, this is adequate but not exceptional.

    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, front-loaded sentence with no redundant words. Every part serves a purpose, making it highly efficient for quick understanding.

    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?

    While the tool is simple, the description does not explain the return format, which is essential given no output schema. Users are left to infer what the response contains, causing potential ambiguity.

    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 schema already describes the 'coins' parameter with 100% coverage, but the description adds value by providing concrete examples ('bitcoin, ethereum'), which helps agents understand the format better than the schema alone.

    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 'Get', the resource 'current USD prices for coins', and the input parameter 'CoinGecko ID'. It effectively distinguishes from sibling tools like 'find_arbitrage' and 'scan_top_coins' by specifying the exact data it retrieves.

    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 when current prices are needed, but lacks explicit guidance on when to use this tool versus alternatives, and 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 carries full burden. It discloses the N+1 API call pattern and rate limit concern, which is valuable. However, it does not mention read-only nature, error handling on rate limit, or response format.

    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: first states purpose, second adds behavioral context. No wasted words, front-loaded with action and resource.

    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 two-parameter tool, the description covers purpose and a key behavioral note. However, it omits what the output represents (arbitrage opportunities? details?) and lacks guidance on prerequisites or error states.

    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%, so the schema already defines both parameters clearly. The description adds context about API calls but does not clarify parameter semantics beyond schema defaults and ranges.

    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 specifies the verb 'scan', the resource 'top N coins by market cap', and the outcome 'for cross-exchange arbitrage spreads above a threshold'. It clearly distinguishes from siblings 'get_coin_prices' and 'find_arbitrage' by focusing on top coins and threshold screening.

    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 warns about N+1 API calls and rate limits, guiding users to be mindful when invoking. It implies that this tool is for quick screens of top coins, but does not explicitly state when to use alternatives like 'find_arbitrage' for broader searches.

    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

mcp-crypto-arbitrage MCP server

Copy to your README.md:

Score Badge

mcp-crypto-arbitrage 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/abe-source/mcp-crypto-arbitrage'

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