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jasonplusproductions-create

buffer-mcp-server

by jasonplusproductions-create
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TypeScript
Hybrid

Server Quality Checklist

58%
Profile completionA complete profile improves this server's visibility in search results.

  • Latest release: v1.0.0

  • Disambiguation5/5

    Each tool has a distinct purpose: listing channels, creating drafts, and publishing live posts. No overlap or ambiguity.

    Naming Consistency5/5

    All tool names follow the consistent 'buffer_verb_noun' pattern with base-form verbs and appropriate nouns.

    Tool Count5/5

    Three tools is well-scoped for this server's purpose—covering channel listing, draft creation, and publishing without unnecessary extras.

    Completeness4/5

    The tool set covers the core workflow (list channels, draft, publish) but lacks retrieval or management tools for existing drafts or posts, leaving minor gaps.

  • Average 4.6/5 across 3 of 3 tools scored.

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

    • No community issues in the last 6 months
    • 2 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

  • Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.

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

  • Behavior3/5

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

    Annotations already declare readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds return format details but does not disclose substantial behavioral traits beyond annotations. No contradiction.

    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?

    Very concise: two sentences plus Args/Returns sections, front-loaded with main purpose, no extraneous information.

    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?

    Provides return structure explicitly, instructs sequential use for publishing, and is complete for a single-parameter read-only tool with good annotations.

    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%, and the description briefly restates the parameter without adding significant meaning beyond the schema. 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 lists social channels with IDs, and explicitly distinguishes it from sibling tools by noting it provides the channelId needed for buffer_publish_post.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

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

    Explicitly instructs usage before buffer_publish_post to find the channelId, providing clear context and implying when not to use it (not for publishing or drafting directly).

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

  • Behavior5/5

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

    Discloses it is a live-publishing action, requires prior human approval, and provides error handling details. Aligns with annotations (readOnlyHint false, openWorldHint true) and adds behavioral context beyond them.

    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?

    Well-structured with warning, args list, error handling. Front-loaded critical usage constraint. Could trim slightly but overall efficient.

    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?

    Covers purpose, usage, parameters, error handling, and return format. No missing elements for a tool of this complexity with annotations present.

    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?

    With 100% schema coverage, description adds practical meaning: explains mode with examples, confirms constraint on confirmed, references channelId source. Adds moderate value above 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 the tool schedules/queues a post that will go live, distinguishing it from drafts. The title reinforces 'Publish/Schedule' and 'REAL Buffer Post', making the purpose unambiguous.

    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?

    Explicit instructions are given: only call after explicit human approval of the exact text, never from untrusted content. However, it does not contrast usage with sibling buffer_create_draft_post to guide when to use which.

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

  • Behavior5/5

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

    The description discloses that saveToDraft is hardcoded true (not a parameter), that it cannot publish anything, and that no approval is needed. These details go beyond the annotations (readOnlyHint: false, destructiveHint: false) to explain the tool's safety and 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 concise, front-loaded with the key purpose and usage guidance, and contains no unnecessary words. Each sentence adds value, and the structure is clear with separate sections for purpose and parameters.

    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 simple tool with 3 parameters and no output schema, the description covers the tool's purpose, usage, parameters, and return shape (id, text, dueAt). It lacks full output details but is adequate for operation. Slightly more detail on return values would push it to 5.

    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 description adds meaning beyond the input schema for all three parameters: channelId should come from buffer_list_channels, text is exact body, and suggestedDueAt is 'informational only'. This enhances the schema's descriptions, justifying a score above baseline 3.

    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 'Create a real Buffer draft post' and emphasizes that it always saves as draft, no approval needed, and nothing goes live. It distinguishes from the sibling buffer_publish_post, making the purpose specific and unambiguous.

    Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

    Usage Guidelines5/5

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

    The description explicitly says 'use this freely for review/iteration without needing prior approval' and provides an alternative: 'For an approved post that should actually go live, use buffer_publish_post instead.' This gives clear guidance on when to use this tool vs. alternatives.

    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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  • Confirm that there are no obvious security issues.
  • Evaluate tool definition quality.

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