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ekelly95

document-index-mcp

by ekelly95

Server Configuration

Describes the environment variables required to run the server.

NameRequiredDescriptionDefault
DOCUMENT_INDEX_OCRNoOCR mode: auto or off. Default: auto.auto
DOCUMENT_INDEX_OCR_LANGNoOCR language. Default: eng.eng
DOCUMENT_INDEX_MAX_FILE_MBNoMaximum file size in MB. Files above this are refused. Raise it with --max-file-mb= or this environment variable. Default: 512.512
DOCUMENT_INDEX_OCR_WORKERSNoOCR workers. Default: 2.2
DOCUMENT_INDEX_LIBRARY_PATHYesLibrary root: one folder holding the documents you want indexed. It is a security boundary — the server refuses to read anything outside it, including through a symlink that lexically passes but physically escapes.
DOCUMENT_INDEX_OCR_LANG_PATHNoPath to tessdata_fast language files. Default: the CDN.

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

CapabilityDetails
tools
{
  "listChanged": true
}
prompts
{}
resources
{}

Tools

Functions exposed to the LLM to take actions

NameDescription
search_documentA

Hybrid BM25 + semantic search across ingested documents. Returns ranked snippets with precise locators (page or section, section path, bbox). This is the usual starting point. It never returns full text — follow a hit with get_chunk_context using its chunk_id to read.

get_document_outlineA

Hierarchical heading tree with locators and chunk seq spans. Costs almost no context — use it to orient before targeted get_chunk_context reads, and jump straight to a section with document_id + chunk_seq_start. Never returns body text. Call it with no document_id to list the library. It also reports ingest progress: a document still being indexed shows status 'processing' with a rising chunk_count.

get_chunk_contextA

Full text of one chunk plus up to 5 neighbours on each side in reading order. Address it by chunk_id (from search results) OR by document_id + seq (from outline spans). This is the only tool that returns body text and it is hard-capped at ~24k characters — walk seq windows to read progressively.

ingest_documentA

Index a file from the library into the retrieval index. PDF, DOCX, Markdown and plain text are ingestible in this build; EPUB, PowerPoint, HTML and legacy binary Office (.doc) are recognised and refused with a reason naming the remedy. Scanned PDFs are detected and OCR'd automatically — expect those to index slowly, a few seconds per page. Format is decided by content rather than extension, which is why a mislabelled file is still routed correctly. Returns immediately with a document_id while indexing continues in the background — poll get_document_outline with that id to watch chunk_count rise and see when status becomes 'ready'. Re-ingesting an identical file is a no-op and returns the existing document_id.

delete_documentA

Remove a document from the index: its chunks, its full-text entries and its vectors. The source file on disk is never touched. Use it to drop something ingested by mistake — an edited file does NOT need this, because re-ingesting one already replaces the version it supersedes. Deletion is permanent; the document's chunk_ids stop resolving, and re-ingesting the file rebuilds it.

Prompts

Interactive templates invoked by user choice

NameDescription

No prompts

Resources

Contextual data attached and managed by the client

NameDescription

No resources

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