302AI File Parser MCP Server
Click on "Install Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@302AI File Parser MCP Serverparse the quarterly report PDF and summarize key findings"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
302AI File Parser MCP Server
Development
Install dependencies:
npm installBuild the server:
npm run buildFor development with auto-rebuild:
npm run watchRelated MCP server: cc-session-search
Installation
To use with Claude Desktop, add the server config:
On MacOS: ~/Library/Application Support/Claude/claude_desktop_config.json
On Windows: %APPDATA%/Claude/claude_desktop_config.json
{
"mcpServers": {
"302ai-file-parser-mcp": {
"command": "npx",
"args": ["-y", "@302ai/file-parser-mcp"],
"env": {
"302AI_API_KEY": "YOUR_API_KEY_HERE"
}
}
}
}Find Your 302AI_API_KEY here
Debugging
Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the MCP Inspector, which is available as a package script:
npm run inspectorThe Inspector will provide a URL to access debugging tools in your browser.
Available Tools
1 toolparseFileToTextC
Provide a file url, parse the file to text, return the text as a string.
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Public URL of the source file, supports pdf/docx/csv/txt/html/odt/rtf/epub/md/xml/xsl/pptx/potx/js/cs |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden. It mentions parsing and returning text, but doesn't disclose critical behavioral traits: supported file formats (covered in schema), parsing limitations (e.g., large files, encoding issues), error handling, or performance characteristics. The description is too vague about how parsing works and what happens in edge cases.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is concise and front-loaded in a single sentence: 'Provide a file url, parse the file to text, return the text as a string.' It efficiently states the core functionality without unnecessary words. However, it could be slightly more structured by separating input, action, and output more clearly.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given no annotations and no output schema, the description is incomplete for a tool that performs file parsing. It doesn't explain the return value format beyond 'as a string' (e.g., structured text, encoding), doesn't mention potential errors or limitations, and lacks details on behavioral aspects. For a tool with 1 parameter but complex underlying functionality, this leaves significant gaps.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so the schema fully documents the single parameter 'url' with its type and supported formats. The description adds no additional meaning beyond what's in the schema—it merely repeats 'Provide a file url' without extra context. This meets the baseline of 3 when schema coverage is high.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'parse the file to text, return the text as a string.' It specifies the action (parse) and resource (file), and mentions the input (file url) and output (text string). However, it doesn't distinguish from siblings since none exist, so it can't achieve the full 5-point differentiation.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides minimal usage guidance: 'Provide a file url' indicates when to use it, but offers no context about when not to use it or alternatives. With no sibling tools, it can't specify alternatives, but it lacks any prerequisites, limitations, or error conditions that would help an agent decide appropriateness.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
TDQS
With only one tool, there is no possibility of ambiguity or overlap between tools. The tool's purpose is clearly distinct as it is the sole operation available.
The single tool name follows a clear verb_noun pattern (parseFileToText), and with only one tool, consistency is inherently perfect as there are no other names to compare against.
A single tool is generally too few for a server named 'File Parser', as this suggests a domain that might include operations like parsing different file types, handling errors, or extracting metadata. The scope feels incomplete with just one basic parsing function.
The server's name implies a broader file parsing capability, but the tool set only includes parsing files to text. Obvious gaps include support for different file formats (e.g., PDF, DOCX), structured data extraction, or error handling, making the surface severely incomplete for the apparent purpose.
Resources
Unclaimed servers have limited discoverability.
Looking for Admin?
If you are the server author, to access and configure the admin panel.
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