As Help Mcp

AS Help MCP Server

MCP server for B&R Automation Studio help documentation search. Provides keyword search by default using LanceDB's native full-text search (FTS), and optional hybrid semantic + keyword search using Reciprocal Rank Fusion (RRF) when an embedding API is configured.

Features

• Keyword search (default): Fast full-text search using LanceDB's native FTS — no external dependencies
• Hybrid search (optional): RRF fusion of vector similarity and keyword matching when embeddings are enabled
• API-based embeddings: Works with any OpenAI-compatible endpoint (Ollama, OpenAI, Azure OpenAI, GitHub Models, LiteLLM) — no local ML models required
• Smart ranking: Query-type detection shifts weights between FTS and vectors (identifiers like MC_MoveAbsolute favor exact match; natural language favors semantic similarity)
• Category filtering and hierarchical browsing
• Auto-generated links to B&R online help (AS4/AS6)
• HelpID lookup for context-sensitive help integration
• Incremental reindexing — only changed pages are re-processed (works with both FTS-only and hybrid tables)
• Graceful degradation — if embedding API fails, keyword search remains available
• Security hardened — path traversal prevention, LIKE wildcard injection protection, UTF-8 safe string handling

Prerequisites

• B&R Automation Studio installed (or its help files copied/mounted on macOS)
• VS Code with GitHub Copilot extension
• For standalone binary: Download the Windows .exe or macOS Apple Silicon binary from [Releases](../../releases) — no build tools required
• For building from source: Rust 1.91+
• Optional (for hybrid search): An OpenAI-compatible embedding API (e.g., Ollama with nomic-embed-text)

Quick Start (VS Code)

Add to .vscode/mcp.json in your workspace:

Option 1: Standalone Binary (Recommended)

Download the platform-appropriate binary from [Releases](../../releases). Windows users should place the .exe in %APPDATA%\as-help-mcp\.

{
  "servers": {
    "as-help": {
      "command": "${env:APPDATA}\\as-help-mcp\\as-help-server.exe",
      "args": [
        "--help-root",
        "C:\\Program Files (x86)\\BRAutomation\\AS6\\Help-en\\Data",
        "--db-path",
        "${env:APPDATA}\\as-help-mcp\\data\\as6\\.ashelp_lance",
        "--metadata-dir",
        "${env:APPDATA}\\as-help-mcp\\data\\as6\\.ashelp_metadata",
        "--as-version",
        "6"
      ]
    }
  }
}

Update --help-root to match your AS installation:

• AS 4.x: C:\\BRAutomation\\AS412\\Help-en\\Data
• AS 6.x: C:\\Program Files (x86)\\BRAutomation\\AS6\\Help-en\\Data

On Apple Silicon macOS, download as-help-server-macos-arm64, make it executable, and place it somewhere on your PATH:

mkdir -p ~/.local/bin
cp ~/Downloads/as-help-server-macos-arm64 ~/.local/bin/
chmod +x ~/.local/bin/as-help-server-macos-arm64

Then use it in .vscode/mcp.json:

{
  "servers": {
    "as-help": {
      "command": "/Users/you/.local/bin/as-help-server-macos-arm64",
      "args": [
        "--help-root",
        "/Users/you/AS6/Help-en/Data",
        "--db-path",
        "/Users/you/.ashelp/data/as6/.ashelp_lance",
        "--metadata-dir",
        "/Users/you/.ashelp/data/as6/.ashelp_metadata",
        "--as-version",
        "6"
      ]
    }
  }
}

Option 2: Build from Source

git clone 
cd as-help-mcp

On macOS, install the required Protocol Buffers compiler first:

brew install protobuf

Then build:

cargo build --release

The binary is at target/release/as-help-server on macOS or target/release/as-help-server.exe on Windows.

{
  "servers": {
    "as-help": {
      "command": "C:\\path\\to\\as-help-mcp\\target\\release\\as-help-server.exe",
      "args": [
        "--help-root",
        "C:\\Program Files (x86)\\BRAutomation\\AS6\\Help-en\\Data",
        "--db-path",
        "C:\\path\\to\\data\\.ashelp_lance",
        "--metadata-dir",
        "C:\\path\\to\\data\\.ashelp_metadata",
        "--as-version",
        "6"
      ]
    }
  }
}

---

Restart VS Code, then test in Copilot Chat: "Search AS help for mapp Motion"

First run takes 2-3 minutes to build the keyword search index. Subsequent starts are instant (~3s).

---

Enabling Hybrid Search (Optional)

By default, the server uses keyword-only search (FTS). To enable hybrid semantic + keyword search, configure an OpenAI-compatible embedding API.

Example: Ollama (Local, Free)

1. Install Ollama and pull an embedding model:

ollama pull nomic-embed-text

1. Add --create-embeddings true and embedding environment variables to your MCP config:

{
  "servers": {
    "as-help": {
      "command": "${env:APPDATA}\\as-help-mcp\\as-help-server.exe",
      "args": [
        "--help-root", "C:\\Program Files (x86)\\BRAutomation\\AS6\\Help-en\\Data",
        "--db-path", "${env:APPDATA}\\as-help-mcp\\data\\as6\\.ashelp_lance",
        "--metadata-dir", "${env:APPDATA}\\as-help-mcp\\data\\as6\\.ashelp_metadata",
        "--as-version", "6",
        "--create-embeddings", "true"
      ],
      "env": {
        "EMBEDDING_API_ENDPOINT": "http://localhost:11434",
        "EMBEDDING_API_KEY": "ollama",
        "EMBEDDING_MODEL": "nomic-embed-text",
        "EMBEDDING_DIMENSIONS": "768",
        "EMBEDDING_BATCH_SIZE": "100",
        "EMBEDDING_MAX_CHARS": "4000"
      }
    }
  }
}

Any OpenAI-compatible endpoint works — OpenAI, Azure OpenAI, GitHub Models, LiteLLM, etc.

How Hybrid Search Works

When embeddings are enabled, the server uses Reciprocal Rank Fusion (RRF) to combine four search signals:

| Signal | NL Weight | ID Weight | Description | |--------|-----------|-----------|-------------| | Title vector | 2.0 | 0.5 | Semantic similarity between query and title+breadcrumb embeddings | | Content vector | 1.0 | 0.5 | Semantic similarity between query and breadcrumb+content embeddings | | FTS keyword | 1.5 | 3.0 | Lance native full-text search on title+breadcrumb+content | | Title match | 3.0 | 4.0 | Exact/substring match of query in page titles | | Breadcrumb match | 2.0 | 3.0 | Query terms in breadcrumb path |

Query-type detection automatically selects weights: identifier queries (e.g., MC_MoveAbsolute, X20DI9371) shift toward FTS + title match; natural language queries favor vector similarity.

For a deep dive into the RAG architecture, see [RAG.md](RAG.md).

---

CLI Arguments

Run as-help-server --help for full details.

| Argument | Env Var Equivalent | Description | |----------|--------------------|-------------| | --help-root | AS_HELP_ROOT | Path to AS Help Data folder | | --db-path | AS_HELP_DB_PATH | Path to the LanceDB directory | | --metadata-dir | AS_HELP_METADATA_DIR | Path to the indexing metadata directory | | --as-version | AS_HELP_VERSION | AS version for online help (4 or 6) | | --force-rebuild | AS_HELP_FORCE_REBUILD | Force a full index rebuild | | --create-embeddings | CREATE_EMBEDDINGS | Enable API-based embeddings for hybrid search |

Transport Configuration (Environment Variables)

| Variable | Default | Description | |----------|---------|-------------| | MCP_TRANSPORT | stdio | Transport mode: stdio or streamable-http (SSE is explicitly rejected with a helpful error) | | MCP_HOST | 127.0.0.1 | Host to bind for streamable-http transport | | MCP_PORT | 8000 | Port to bind for streamable-http transport | | MCP_DISABLE_DNS_REBINDING_PROTECTION | false | Disable DNS rebinding protection for streamable-http (allows non-loopback hosts) |

Embedding Configuration (Environment Variables)

These are only needed when --create-embeddings true is set:

| Variable | Default | Description | |----------|---------|-------------| | EMBEDDING_API_ENDPOINT | (required) | Base URL of OpenAI-compatible API | | EMBEDDING_API_KEY | (required) | API key / bearer token | | EMBEDDING_MODEL | (required) | Model name (e.g., nomic-embed-text, text-embedding-3-small) | | EMBEDDING_DIMENSIONS | (required) | Vector dimensions (e.g., 768, 1536) | | EMBEDDING_BATCH_SIZE | 100 | Texts per API call | | EMBEDDING_MAX_CHARS | 8000 | Truncate input texts to this length |

---

Development

Building

cargo build          # Debug build
cargo build --release  # Optimized release build

Testing

cargo test

Project Structure

src/
  main.rs           # Entry point, transport setup (stdio + StreamableHTTP)
  server.rs         # FastMCP server, tool/prompt handlers
  indexer.rs        # XML parsing, HTML text extraction, breadcrumbs
  search_engine.rs  # LanceDB FTS + hybrid search with RRF
  embeddings.rs     # Optional API-based embedding service
  config.rs         # CLI args + env var configuration
  models.rs         # Shared data types

---

Performance

| Operation | Time | Notes | |-----------|------|-------| | XML parse | ~2s | 58K+ pages in-memory | | First index build (FTS-only) | ~2-3 min | Parallel HTML extraction + FTS indexing | | First index build (hybrid) | 15-20 min | + embedding via API | | Subsequent startup | ~3s | Load existing index | | Search query | 10-50ms | RRF hybrid or FTS keyword |

---

Tools

| Tool | Description | |------|-------------| | search_help | Hybrid semantic + keyword search with RRF ranking and optional category filter | | get_categories | List top-level categories for filtering | | browse_section | Navigate help tree hierarchically | | get_page_by_id | Get full page content | | get_page_by_help_id | Retrieve page by numeric HelpID | | get_breadcrumb | Get navigation path | | get_help_statistics | Get content and index build statistics |

Prompts

| Prompt | Description | |--------|-------------| | help_search | Structured search with page IDs, breadcrumbs, and HelpIDs | | help_details | Deep research with content synthesis from multiple pages |

---

Multiple AS Versions

{
  "servers": {
    "as-help-4": {
      "command": "${env:APPDATA}\\as-help-mcp\\as-help-server.exe",
      "args": [
        "--help-root", "C:\\BRAutomation\\AS412\\Help-en\\Data",
        "--db-path", "${env:APPDATA}\\as-help-mcp\\data\\as4\\.ashelp_lance",
        "--metadata-dir", "${env:APPDATA}\\as-help-mcp\\data\\as4\\.ashelp_metadata",
        "--as-version", "4"
      ]
    },
    "as-help-6": {
      "command": "${env:APPDATA}\\as-help-mcp\\as-help-server.exe",
      "args": [
        "--help-root", "C:\\Program Files (x86)\\BRAutomation\\AS6\\Help-en\\Data",
        "--db-path", "${env:APPDATA}\\as-help-mcp\\data\\as6\\.ashelp_lance",
        "--metadata-dir", "${env:APPDATA}\\as-help-mcp\\data\\as6\\.ashelp_metadata",
        "--as-version", "6"
      ]
    }
  }
}

License

MIT

Source & license

This open-source MCP server is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: br-automation-community
• Source: br-automation-community/as-help-mcp
• License: MIT

Install and usage instructions live in the source repository linked above.