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iflow-mcp

SentryFrogg MCP Server

by iflow-mcp

Server Quality Checklist

67%
Profile completionA complete profile improves this server's visibility in search results.
  • Latest release: v4.2.0

  • Disambiguation5/5

    Each tool targets a completely distinct domain: HTTP API calls, PostgreSQL database management, and SSH remote execution. There is no overlap in purpose or functionality, so an agent can clearly differentiate them.

    Naming Consistency5/5

    All tool names follow the pattern 'mcp_<domain>_<role>' (e.g., mcp_api_client, mcp_psql_manager, mcp_ssh_manager), using consistent snake_case and a descriptive prefix. The variation between 'client' and 'manager' is appropriate for their roles.

    Tool Count3/5

    With only three tools, the server covers three broad areas (API, database, SSH). While each tool is rich in sub-actions, the raw count is at the low end of the range, making it borderline but acceptable for a general-purpose server.

    Completeness4/5

    Within the declared domains, the tools provide comprehensive coverage: HTTP client supports all methods, PostgreSQL manager includes full CRUD and schema inspection, SSH manager handles command execution and system info. Minor gaps like bulk operations exist but do not hinder core workflows.

  • Average 3.7/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 0 commits in the last 12 weeks
    • No stable releases found
    • 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.

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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 must cover behavioral traits. It includes key details like secret encryption and the automatic LIMIT 100 addition in quick_query. However, it does not disclose the nature of mutating actions (insert, update, delete) as potentially destructive or reversible, nor does it mention error handling or concurrency.

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

    Conciseness3/5

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

    The description is a single dense paragraph that front-loads the key flow but then delves into setup_profile parameter details. It could be more structured (e.g., bullet points for actions) without being overly verbose. It is concise but at the cost of clarity.

    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 (22 parameters, many actions, no output schema), the description provides a reasonable overview including the flow and key behaviors. However, it lacks information on return values for each action and has gaps in parameter explanations, making it adequate but not 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?

    The description adds meaning beyond the input schema for some parameters, such as the params array for $ placeholders and the automatic LIMIT in quick_query. However, with only 41% schema description coverage, many parameters remain unexplained. The description partially compensates but not fully.

    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 it is a PostgreSQL toolchain and lists the specific actions available, distinguishing it from sibling tools (API client, SSH manager) by domain. The purpose is well-defined with a clear flow: setup_profile then action.

    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 explains the required flow (setup_profile first), which implies usage guidance, but does not explicitly state when not to use this tool or provide comparisons to alternatives. For example, it does not advise against using destructive actions without caution.

    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?

    The description discloses key behaviors: data encryption for credentials, sequential per-profile execution, and no concurrency. With no annotations provided, this is adequate but lacks details on error handling, return values, or auth requirements.

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

    Conciseness3/5

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

    The description is relatively concise but poorly structured, appearing as a run-on sentence listing actions. It could be improved with bullet points or clearer separation of action descriptions.

    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 tool's complexity (11 parameters, no output schema), the description lacks essential details about host/port/timeout parameters and return values. It covers actions but not the full parameter context needed for correct invocation.

    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 coverage is low (18%). The description adds meaning for a few parameters (password, private_key, passphrase in setup_profile) but fails to describe host, port, username, timeouts, etc. It does not sufficiently compensate for the low schema coverage.

    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 an 'SSH executor' and lists specific actions (setup_profile, list_profiles, execute, system_info, check_host), distinguishing it from sibling tools mcp_api_client and mcp_psql_manager 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 Guidelines4/5

    Does the description explain when to use this tool, when not to, or what alternatives exist?

    The description provides clear context for each action, including constraints like sequential execution and no concurrent runs. However, it does not explicitly state when to use this tool versus alternatives or when not to use it.

    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?

    The description discloses key behaviors: auth_token is prefixed into Authorization header unless overridden, local URLs are allowed, and responses are structured results or MCP errors. However, it lacks disclosures about potential risks (e.g., local URL access), rate limits, or idempotency of actions.

    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 very concise: two sentences that front-load the purpose ('HTTP caller') and efficiently explain all parameters and behaviors without unnecessary words.

    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?

    The description covers all parameters and key behaviors, and mentions response format ('structured results or MCP errors'). However, without an output schema, more detail on response structure would improve completeness.

    Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

    Parameters5/5

    Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

    With 0% schema description coverage, the description fully compensates by explaining all five parameters: action enum, url requirement, data for mutating verbs, headers as string map, and auth_token behavior. This adds significant meaning beyond the bare schema.

    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 an HTTP caller, lists all six supported actions (get, post, put, delete, patch, check_api), and specifies that it makes HTTP requests. It is distinct from sibling tools (database and SSH managers) by focusing on HTTP calls.

    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 making HTTP requests by explicitly detailing action verbs and parameters. However, it does not provide explicit when-to-use or when-not-to-use guidance, though the sibling tools are sufficiently different that confusion is unlikely.

    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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