pdf-merger-mcp-server
Server Quality Checklist
Latest release: v2.0.0
- Disambiguation5/5
Each tool has a clearly distinct purpose: upload, remove, merge, and get download URL. There is no overlap in functionality, and the descriptions reinforce the boundaries between them.
Naming Consistency5/5All tool names follow a consistent prefix+verb_noun pattern (pdf_merger_remove_file, pdf_merger_upload_pdfs, pdf_merger_get_download_url). The single exception, pdf_merger_merge, is still a clear verb and fits the overall style.
Tool Count5/5Four tools is a well-scoped size for a PDF merging service. Each tool covers a necessary step in the workflow without redundancy or bloat.
Completeness4/5The core workflow (upload, remove, merge, download) is covered. However, there is no tool to list the current files in a session, which would be needed if an agent needs to reference file IDs without having just uploaded them. This is a minor but notable gap.
Average 4.6/5 across 4 of 4 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 is passing
Add a LICENSE file by following GitHub's guide. Once GitHub recognizes the license, the system will automatically detect it within a few hours.
If the license does not appear after some time, you can manually trigger a new scan using the MCP server admin interface.
MCP servers without a LICENSE cannot be installed.
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.jsonto 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
- Behavior5/5
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations mark the tool as destructive (destructiveHint: true), but the description strengthens this by stating the file is permanently deleted from cloud storage and cannot be undone. It also documents error handling (404 for missing session/file), providing additional behavioral detail beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with clear sections for purpose, consequence, arguments, return value, and errors. Each sentence provides necessary information without padding.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple destructive 2-parameter tool, the description covers the operation's effect (permanent deletion), the exact return JSON, and error conditions. No output schema is present, but the description compensates by explicitly specifying the return value.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Both parameters (session_id and file_id) have full schema descriptions, and the description's Args section essentially restates the schema. No additional syntax, precedence, or format details are provided, so the description adds no semantic value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action: remove a single PDF file from an upload session. The verb 'Remove' and resource 'PDF file from an upload session' are specific and distinct from sibling tools that upload, merge, or generate download links.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines3/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool is for deleting a file from a session but does not explicitly state when to choose it over alternatives or when not to use it. No exclusion or alternative tool is mentioned, leaving usage context implicit rather than explicit.
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?
Beyond the annotations (which indicate non-read-only, non-idempotent, non-destructive), the description adds substantial behavioral context: file size limit, file count limit, error handling for missing files/non-PDF/oversized/exceeding limits, and session creation/appending behavior. This is far beyond what annotations provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well-structured with sections for description, args, return value, examples, and error handling. Every sentence adds necessary information without redundancy or fluff. It is appropriately sized for the tool's complexity.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness4/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description is highly complete given the lack of an output schema: it specifies the return JSON structure, examples, and error cases. Minor gaps exist, such as not specifying behavior for an invalid session_id, but overall it is sufficient for an agent to use the tool correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema already covers both parameters with descriptions (100% coverage), but the tool description adds value by including concrete examples, clarifying the session_id append-vs-new behavior, and explaining the expected file_paths format. This lifts it above the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool uploads one or more PDF files to the PDF Merger service for later merging, using a specific verb and resource. It distinguishes itself from sibling tools (remove, merge, download URL) by focusing solely on the upload action.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear context for when to use the tool (starting a session or appending to an existing one) and explains the session_id behavior. However, it does not explicitly contrast with alternative tools, so a 4 rather than 5 is appropriate.
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?
Annotations already declare readOnly, idempotent, and non-destructive. The description adds critical behavioral context: tokens are one-time use, the link expires after first download, and associated cloud files are cleaned up. It also notes that opening the URL triggers a download of 'merged.pdf' and source blobs are deleted. This goes well beyond the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is efficiently organized with a summary, args, returns, and notes. Every sentence adds value, and the most important information is front-loaded. No redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple single-parameter tool, the description fully covers preconditions, behavior, return format, and side effects. Even without an output schema, it outlines the return JSON. Complete and self-sufficient.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters4/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 100% with a well-described token parameter. The description reinforces the source ('from the merge response') and one-time nature, adding context not present in the schema. Slight value beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb+resource: 'Build a one-time download URL for a merged PDF.' This clearly distinguishes it from sibling tools (merge, upload, remove) and states exactly what the tool does.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines4/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The description explicitly states the prerequisite: 'The token is returned by pdf_merger_merge.' This tells the agent when to use the tool, though it does not explain exclusions or when not to use it. The context is clear enough for correct deployment.
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?
Beyond annotations, the description discloses that the session is consumed after merging, that the returned token is one-time, and includes specific HTTP error codes for failure modes. This is substantial behavioral context not present in the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Conciseness5/5Is the description appropriately sized, front-loaded, and free of redundancy?
The description is well structured with focused sections: overview, return value, workflow, and error handling. Each section adds necessary information, and the most important purpose statement is front-loaded.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Completeness5/5Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Despite lacking an output schema, the description provides a concrete JSON return example, full workflow guidance, and error handling details. This gives the agent enough context to invoke the tool correctly and interpret results.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Parameters3/5Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Input schema coverage is 100%, and the schema already describes both parameters, including min/max items and the ordering behavior. The description repeats this information without adding new parameter-level meaning, so baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Purpose5/5Does the description clearly state what the tool does and how it differs from similar tools?
The description opens with a specific verb and resource: "Merge previously uploaded PDFs in a specified order into a single PDF." It clearly distinguishes this from sibling tools by naming the upload, remove, and download steps.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Usage Guidelines5/5Does the description explain when to use this tool, when not to, or what alternatives exist?
The Workflow section explicitly lists the sequence of operations (upload → remove optional → merge → download) and mentions the one-time session constraint, which tells the agent when to use this tool and when re-uploading is needed.
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
Copy to your README.md:
Score Badge
Copy to your README.md:
Latest Blog Posts
- Who's Calling? MCP Hosts Are an Identity Blind Spot (And the Spec Knows It)By Om-Shree-0709 on .mcpAgent IdentityOAuth 2.1
- Your AI Chatbot Just Exposed Your CEO's Salary to an InternBy Om-Shree-0709 on .Agent IdentityMCP SecurityOAuth Delegation
- Why MCP Servers Need Execution Sandboxing (And Why Your Current Stack Isn't Enough)By Om-Shree-0709 on .Agentic AiPrompt InjectionWebAssembly
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/NikhilBelwate/pdf-merger-mcp-server'
If you have feedback or need assistance with the MCP directory API, please join our Discord server