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scream687

universal-context-mcp

by scream687
OverviewSchemaRelated ServersScoreDiscussions
JavaScript
Hybrid

Server Quality Checklist

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

  • Latest release: v1.0.0

  • Disambiguation5/5

    The two tools have clearly distinct purposes: one loads context, the other saves context. There is no functional overlap.

    Naming Consistency5/5

    Both tools follow a consistent verb_noun pattern using snake_case, with 'bootstrap' and 'export' as clear verbs and 'session_context' as the common noun.

    Tool Count3/5

    With only two tools, the server feels minimal. While it covers the core load/save operations, a broader scope might include additional tools for listing or managing contexts.

    Completeness3/5

    The tool set provides basic load and save capabilities, but lacks operations for initializing, deleting, or listing contexts, leaving minor gaps in lifecycle coverage.

  • Average 3.6/5 across 2 of 2 tools scored.

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

    • No community issues in the last 6 months
    • 9 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.

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    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.

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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 exist, so description must disclose behavioral traits. It mentions aggregation and saving to clipboard/ledger but does not explain if the operation is idempotent, what happens to previous context, permission requirements, rate limits, or 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.

    Conciseness4/5

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

    Single sentence with front-loaded action ('SAVE context') and concise enumeration of aggregated elements. Slightly improved structure could separate purpose from details, but overall no waste.

    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 no output schema and no annotations, the description lacks detail on return values, error handling, behavior when parameters are omitted, and impact on shared resources. For a tool that modifies state ('SAVE'), completeness 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?

    Schema description coverage is 100%; both parameters have clear schema descriptions. The tool description rephrases 'handoff_message' and 'cloud_sync' but adds no new meaning beyond the schema's own descriptions.

    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 action 'SAVE context' and specifies what is aggregated (project metadata, tree, diffs, mental model) and where it goes (clipboard and ledger). This distinguishes from sibling bootstrap_session_context which likely initializes context.

    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 exporting context but provides no explicit guidance on when to use vs. the sibling tool, no when-not-to-use scenarios, and no prerequisites or alternatives.

    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 solely indicates fetching (a read operation) from the ledger. It does not disclose any side effects, authentication needs, or rate limits, but for a simple tool with no parameters, the basic trait is conveyed.

    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 a single sentence, concise without fluff. The 'LOAD context:' prefix is slightly redundant but not detrimental.

    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 and no annotations, the description covers the core action but omits any details about the return format or error conditions, leaving some ambiguity for an agent.

    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?

    There are no parameters, so schema coverage is 100%. According to guidelines, 0 parameters baseline is 4, and the description does not need to add parameter info.

    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 'fetches' and the resource 'latest Shadow Context from the ledger', and states the purpose 'to resume work perfectly'. This clearly distinguishes it from the sibling tool export_session_context, which likely exports context.

    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 resuming work by loading context, but it does not explicitly state when to use this tool versus export_session_context or provide any exclusions or prerequisites.

    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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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.

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