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Llamaparse Mcp

  • 1 installs
  • 16 repo stars
  • Updated August 5, 2026
  • run-llama/mcp-llamaindex-ai

Helps with ai & agent building tasks during AI-assisted development.

About

llamaparse-mcp is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted coding.

  • llamaparse-mcp
  • AI & Agent Building
  • AI-coding skill

Llamaparse Mcp by the numbers

  • 1 all-time installs (skills.sh)
  • Ranked #14,101 of 16,546 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 5, 2026 (Skillselion catalog sync)
npx skills add https://github.com/run-llama/mcp-llamaindex-ai --skill llamaparse-mcp

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Listed on Skillselion
Installs1
repo stars16
Last updatedAugust 5, 2026
Repositoryrun-llama/mcp-llamaindex-ai

What it does

Helps with ai & agent building tasks during AI-assisted development.

Files

SKILL.mdMarkdownGitHub ↗

LlamaParse MCP — Usage Guide

Authentication

All tools require a valid session. If a tool call returns an authentication error, ask the user to re-authenticate before retrying. Do not retry automatically without prompting the user.

Uploading a File

Every operation (parse, classify, split) requires a fileId obtained by uploading first. There are two upload paths — choose based on where the file lives:

  • File accessible via URL — use uploadFileByUrl. Pass the direct download URL and a descriptive file name. This is the preferred path when the user shares a link.
  • Local or binary file — call getUploadUrl first to obtain a pre-signed upload URL and token, then POST the file to the returned endpoint. The token is valid for 10 minutes; complete the upload before it expires.

For getUploadUrl, always set purpose to match the intended downstream operation ('parse', 'classify', 'split', etc.) so the server can apply the right storage policy.

Choosing What to Do with a File

Once you have a fileId, pick the tool that matches the user's goal:

GoalTool
Extract text or markdown contentparseFile
Determine which category a document belongs toclassifyFile
Break a multi-section document into labeled segmentssplitFile

These are independent — you can run any combination on the same fileId.

Parsing

Use parseFile to extract readable content. Choose the tier based on document complexity:

  • cost_effective — fast and cheap; good for standard PDFs with clean text and simple layouts.
  • agentic — slower; use when the document has tables, multi-column layouts, or embedded images that need accurate extraction.
  • agentic_plus — most thorough; reserve for documents where extraction quality is critical and cost/latency are acceptable.

When in doubt, start with cost_effective. Escalate to agentic only if the output is missing content or has structural errors.

Set markdown: true (the default) when the extracted content will be rendered or passed to an LLM. Set it to false when you need plain text without formatting.

Classifying

Use classifyFile when the user wants to route or label a document. Define categories as precisely as possible — vague category descriptions reduce confidence. Include a description that explains what distinguishes each category from the others, not just what it is.

Splitting

Use splitFile when a single document contains multiple logical sections that should be handled separately (e.g., a combined PDF of multiple contracts, or a report with distinct chapters). Define categories by the sections you expect, not by generic document types.

Choose allowUncategorized based on how strict the split needs to be:

  • 'include' (default) — unknown pages are grouped under an uncategorized segment; safe for exploratory use.
  • 'omit' — uncategorized pages are silently dropped; use when you only care about specific sections.
  • 'forbid' — the operation fails if any page cannot be categorized; use when completeness is required.

Chaining Operations

Common multi-step patterns:

  • Classify then parse — classify to confirm the document type, then parse only if it matches the expected category.
  • Split then parse — split a composite document into segments, then call parseFile on each segment's pages separately (re-upload the relevant pages if needed).
  • Upload once, process multiple ways — a single fileId can be passed to parseFile, classifyFile, and splitFile independently; you do not need to re-upload.

Rate Limits

The server enforces a per-user rate limit. If you receive a rate limit error, read the Retry-After value from the response and wait that many seconds before retrying. Do not retry immediately in a loop.

Error Handling

  • If uploadFileByUrl fails, check whether the URL is publicly accessible and the file type is supported.
  • If parseFile returns incomplete content, retry with a higher tier.
  • If classifyFile or splitFile time out, the job may still be running on the server — inform the user rather than re-submitting the same job immediately.

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