mcpField
F
File AI

File AI

Local
github.comFiles & Storage3Updated 18w ago

About File AI

File AI is a read-only MCP server that indexes local documents into structured content with stable anchors. It is for agents that need to inspect, search, and retrieve context from varied document formats without parsing their internals.

Key features

  1. 01Analyze and index local documents
  2. 02Read blocks, chunks, and anchors
  3. 03Search with source anchors
  4. 04Retrieve context around queries
  5. 05List recognized formats and extraction coverage

Use cases

  1. 01Find passages in a local document
  2. 02Ground answers in page or slide locations
  3. 03Retrieve context around a cited anchor
  4. 04Check format support before processing

MCP support

Exposes document analysis, reading, search, and context retrieval as MCP tools, with profiles, outlines, and chunks available as resources. The server is read-only and does not modify source files.

Configuration

Local server config is the same for every client. Copy it into your client’s MCP config file.

mcp.json · Universal config
{
"mcpServers": {
"flyfish-dev-file-ai": {
"command": "npx",
"args": [
"-y",
"@flyfish-dev/file-ai"
]
}
}
}
Run commandnpx -y @flyfish-dev/file-ai

Local servers need a runtime on your machine (e.g. Node.js 18+). Config file locations differ by client; see your client’s docs.

Packages
npm@flyfish-dev/file-ai0.1.1

Tools

5

Saved tool list · updated 2w ago

ParameterTypeRequiredDescription
pathstringYesLocal file path to analyze.
refreshbooleanNoRe-parse even if this path is already cached.
chunkSizeintegerNoTarget chunk size in characters.
chunkOverlapintegerNoChunk overlap in characters.
maxTextLengthintegerNoMaximum text characters per source anchor before chunking.

Details

From the project README

File AI

Read-only document awareness MCP server for agents. File AI uses Flyfish File Viewer core as the source of truth for format recognition, then turns local files into a stable profile, anchors, blocks, chunks, outline, search results, and contextual snippets so an agent can understand document content without reverse-engineering PDF, OOXML, spreadsheet, email, or archive internals.

MCP Registry name: io.github.flyfish-dev/file-ai

Install

Use it directly with npx:

npx -y @flyfish-dev/file-ai

Or install it globally:

npm install -g @flyfish-dev/file-ai
file-ai --transport stdio

MCP Client Config

Stdio:

{
  "mcpServers": {
    "file-ai": {
      "command": "npx",
      "args": ["-y", "@flyfish-dev/file-ai"]
    }
  }
}

Streamable HTTP:

npx -y @flyfish-dev/file-ai --transport http --host 127.0.0.1 --port 8765

Endpoint:

http://127.0.0.1:8765/mcp

Tools

  • doc_analyze: parse a local file and cache a document index.
  • doc_read: read blocks, chunks, or anchors from an existing index or path.
  • doc_search: search cached content with source anchors.
  • doc_context: retrieve nearby blocks around an anchor or query.
  • doc_list_formats: list File Viewer core registry formats, all supported extensions, renderer capabilities, and File AI extractor coverage.

Resources

  • doc://{indexId}/profile
  • doc://{indexId}/outline
  • doc://{indexId}/chunks

Supported Files

File AI recognizes formats through @file-viewer/core/headless, currently covering 206 registered extensions. profile.format is therefore aligned with the same renderer selection used by Flyfish File Viewer.

Content extraction is a separate layer. File AI provides structured awareness for text/code/Markdown/JSON, PDF text, DOCX, XLSX/CSV, PPTX, EML, and archive manifests. Other File Viewer renderer-only formats such as CAD, 3D, media, image, geospatial, drawing, ebook, and data assets are still recognized in profile.format; when no structured text extractor exists yet, File AI returns a profile plus best-effort metadata/text and explicit warnings in profile.warnings and profile.extraction.

Every content block carries an anchor such as a page, slide, worksheet, row range, nested path, or byte/text location. Agents should cite returned anchorId values when making document-grounded claims.

Development

pnpm install
pnpm build
pnpm test
pnpm validate:skill

Run locally:

pnpm dev -- --transport stdio
pnpm dev -- --transport http --port 8765

Publishing

The package includes:

  • npm metadata for @flyfish-dev/file-ai
  • MCP Registry metadata in server.json
  • GitHub Actions workflow .github/workflows/publish-mcp.yml

Release flow:

git tag v0.1.0
git push origin v0.1.0

The workflow publishes the npm package first, then publishes io.github.flyfish-dev/file-ai to the official MCP Registry through GitHub OIDC. The repository must have an NPM_TOKEN secret that can publish @flyfish-dev/file-ai.

The server is read-only. It does not mutate source documents.

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