pageindex-mcp
Server Configuration
Describes the environment variables required to run the server.
| Name | Required | Description | Default |
|---|---|---|---|
| OPENAI_API_KEY | Yes | API key for OpenAI (required for indexing) | |
| OPENAI_BASE_URL | No | Base URL for OpenAI API (e.g., for OpenRouter) | |
| PAGEINDEX_MODEL | No | OpenAI model (default: gpt-4o-2024-11-20) | |
| INDEX_STORE_PATH | No | Where to store JSON indexes (default: ~/.pageindex-store) | |
| PAGEINDEX_REPO_PATH | Yes | Path to cloned PageIndex repository |
Instructions
Guidance the server publishes about itself, which clients place ahead of the tool catalog so the model reads it before choosing anything.
This server publishes no instructions, or was last inspected before Glama recorded them.
Capabilities
Features and capabilities supported by this server
Protocol revision2025-11-25
| Capability | Details |
|---|---|
| tools | {
"listChanged": true
} |
Tools
Functions exposed to the LLM to take actions
| Name | Description |
|---|---|
| index_documentA | Converts a local PDF into a PageIndex hierarchical tree structure. This is a one-time operation per document. Requires: PAGEINDEX_REPO_PATH env var pointing to cloned VectifyAI/PageIndex repo, and OPENAI_API_KEY for tree generation. |
| get_page_contentA | Extracts text content from specific pages or a tree node of an indexed document. Use get_document_tree first to find relevant node_ids, then call this to read the content. Claude Code handles all reasoning — this tool just returns raw text. |
| list_documentsA | Lists all documents in the local PageIndex store with metadata. |
| get_document_treeA | Returns the full hierarchical tree structure of an indexed document. Useful to understand document organization before searching. |
| delete_documentA | Removes a document from the local index store. |
Prompts
Interactive templates invoked by user choice
| Name | Description |
|---|---|
No prompts | |
Resources
Contextual data attached and managed by the client
| Name | Description |
|---|---|
No resources | |
TDQS
Scored across 5 tools
Each tool targets a distinct action: indexing, reading content, listing documents, retrieving structure, and deleting. No overlap or confusion between tools.
All tool names follow a consistent verb_noun snake_case pattern: index_document, get_page_content, list_documents, get_document_tree, delete_document.
With 5 tools, the set is well-scoped for the domain of document indexing and retrieval. Every tool serves a clear, necessary function without redundancy.
The tools cover the full lifecycle of a document in the index: create (index), read (list, tree, content), and delete. No critical operations are missing given the stated purpose.