Lancer - LanceDB CLI and MCP Server Skill

You are a specialist in using lancer , a CLI and MCP server for LanceDB that provides semantic and full-text search with multi-modal support (text and images). This skill provides comprehensive workflows, best practices, and common patterns for document ingestion, search, and table management.

What is Lancer?

lancer is a powerful tool for:

• Semantic search: Find documents by meaning, not just keywords

• Multi-modal support: Index and search both text and images

• LanceDB integration: Efficient vector database storage and retrieval

• Flexible ingestion: Support for multiple file formats (txt, md, pdf, sql, images)

• MCP server mode: Integration with Claude Desktop and other MCP clients

Core Capabilities

• Ingest: Add documents to LanceDB with automatic chunking and embedding

• Search: Semantic similarity search across documents

• Tables: Manage LanceDB tables (list, info, delete)

• Remove: Remove documents from tables

• MCP: Run as Model Context Protocol server

Quick Start

Basic Search

Search all tables

lancer search "how to deploy kubernetes"

Search specific table with more results

lancer search -t docs -l 20 "authentication methods"

Search with similarity threshold

lancer search --threshold 0.7 "error handling patterns"

Basic Ingestion

Ingest a single file

lancer ingest document.md

Ingest a directory

lancer ingest ./docs/

Ingest multiple paths

lancer ingest file1.md file2.pdf ./images/

Document Ingestion

Ingest Command Options

Ingest to specific table

lancer ingest -t my_docs document.md

Ingest with file extension filter

lancer ingest -e md,txt,pdf ./docs/

Ingest from stdin (pipe file paths)

find ./docs -name "*.md" | lancer ingest --stdin

Ingest from file list

lancer ingest --files-from paths.txt

Custom chunk size and overlap

lancer ingest --chunk-size 2000 --chunk-overlap 400 document.md

Supported File Types

Text formats:

• txt

• Plain text files

• md

• Markdown documents

• pdf

• PDF documents

• sql

• SQL scripts

Image formats:

• jpg , jpeg

• JPEG images

• png

• PNG images

• gif

• GIF images

• bmp

• Bitmap images

• webp

• WebP images

• tiff , tif

• TIFF images

• svg

• SVG vector graphics

• ico

• Icon files

Embedding Models

Text models:

Default: all-MiniLM-L6-v2 (fast, good quality)

lancer ingest document.md

Larger model for better quality

lancer ingest --text-model all-MiniLM-L12-v2 document.md

BGE models (better semantic understanding)

lancer ingest --text-model bge-small-en-v1.5 document.md lancer ingest --text-model bge-base-en-v1.5 document.md

Image models:

Default: clip-vit-b-32 (cross-modal text/image)

lancer ingest image.jpg

ResNet50 for image-only search

lancer ingest --image-model resnet50 image.jpg

Advanced: Force specific model:

Force CLIP for text (enables future image additions)

lancer ingest --embedding-model clip-vit-b-32 document.md

Force BGE for performance (text-only)

lancer ingest --embedding-model BAAI/bge-small-en-v1.5 document.md

Ingestion Optimization

Filter by file size

lancer ingest --min-file-size 1000 --max-file-size 10000000 ./docs/

Skip embedding generation (metadata only)

lancer ingest --no-embeddings document.md

Custom batch size for database writes

lancer ingest --batch-size 200 ./large-dataset/

JSON output for scripting

lancer ingest --format json document.md

Search Operations

Search Command Options

Basic search

lancer search "kubernetes deployment"

Search specific table

lancer search -t docs "authentication"

Limit results

lancer search -l 5 "error handling"

Set similarity threshold (0.0-1.0)

lancer search --threshold 0.6 "database migration"

Include embeddings in results

lancer search --include-embeddings "API design"

JSON output

lancer search --format json "machine learning"

Metadata Filters

Single filter (field:operator:value)

lancer search --filter "author:eq:John" "AI research"

Multiple filters

lancer search
--filter "author:eq:John"
--filter "year:gt:2020"
"deep learning"

Available operators:

eq (equals), ne (not equals)

gt (greater than), lt (less than)

gte (greater/equal), lte (less/equal)

in (in list), contains (string contains)

Search Examples

Find recent documentation

lancer search
-t docs
--filter "date:gte:2024-01-01"
-l 10
"API endpoints"

Search by category

lancer search
--filter "category:eq:tutorial"
"getting started"

Multi-criteria search

lancer search
-t technical_docs
--filter "language:eq:python"
--filter "level:eq:advanced"
--threshold 0.7
-l 15
"async programming patterns"

Table Management

List Tables

List all tables

lancer tables list

JSON output

lancer tables list --format json

Table Information

Get table details

lancer tables info my_table

JSON output for scripting

lancer tables info my_table --format json

Delete Table

Delete a table (be careful!)

lancer tables delete old_table

Remove Documents

Remove specific documents from a table

lancer remove -t docs document_id

Remove multiple documents

lancer remove -t docs id1 id2 id3

Configuration

Using Config File

Specify config file

lancer -c ~/.lancer/config.toml search "query"

Set default table in config

lancer -c config.toml ingest document.md

Environment Variables

Set default table

export LANCER_TABLE=my_docs lancer search "query" # Searches my_docs

Set log level

export LANCER_LOG_LEVEL=debug lancer ingest document.md

Log Levels

Error only

lancer --log-level error search "query"

Warning

lancer --log-level warn ingest document.md

Info (default)

lancer --log-level info search "query"

Debug

lancer --log-level debug ingest document.md

Trace (verbose)

lancer --log-level trace search "query"

Common Workflows

Workflow 1: Index Documentation

1. Ingest markdown docs

lancer ingest -t docs -e md ./documentation/

2. Verify ingestion

lancer tables info docs

3. Test search

lancer search -t docs "installation guide"

4. Refine search with threshold

lancer search -t docs --threshold 0.7 -l 5 "configuration"

Workflow 2: Multi-modal Image Search

1. Ingest images with CLIP model

lancer ingest -t images -e jpg,png,webp
--image-model clip-vit-b-32
./photos/

2. Search images with text query

lancer search -t images "sunset over mountains"

3. Search with higher threshold for precision

lancer search -t images --threshold 0.8 "red car"

Workflow 3: Mixed Content Corpus

1. Ingest with CLIP for cross-modal search

lancer ingest -t knowledge_base
--embedding-model clip-vit-b-32
-e md,pdf,jpg,png
./content/

2. Search text and images together

lancer search -t knowledge_base "architecture diagrams"

3. Filter by file type

lancer search -t knowledge_base
--filter "file_type:eq:png"
"system design"

Workflow 4: Batch Ingestion

1. Generate file list

find ./corpus -type f -name "*.md" > files.txt

2. Ingest from list with custom settings

lancer ingest -t corpus
--files-from files.txt
--chunk-size 1500
--chunk-overlap 300
--batch-size 150

3. Verify ingestion

lancer tables info corpus

4. Test search quality

lancer search -t corpus -l 10 "sample query"

Workflow 5: Update Existing Corpus

1. Ingest new documents

lancer ingest -t docs ./new_docs/

2. Search to verify new content

lancer search -t docs "recent feature"

3. Remove outdated documents

lancer remove -t docs old_doc_id

4. Verify final state

lancer tables info docs

Best Practices

1. Choose the Right Embedding Model

For text-only corpora:

Fast and efficient

lancer ingest --text-model all-MiniLM-L6-v2 document.md

Better quality

lancer ingest --text-model bge-base-en-v1.5 document.md

For images or mixed content:

Cross-modal search (text queries → image results)

lancer ingest --embedding-model clip-vit-b-32 content/

2. Optimize Chunk Settings

Short documents (< 500 words):

lancer ingest --chunk-size 500 --chunk-overlap 100 article.md

Long documents (> 2000 words):

lancer ingest --chunk-size 2000 --chunk-overlap 400 book.pdf

Code documentation:

lancer ingest --chunk-size 1000 --chunk-overlap 200 docs/

3. Use Tables to Organize Content

Separate tables by content type

lancer ingest -t api_docs ./api/.md lancer ingest -t tutorials ./tutorials/.md lancer ingest -t images ./screenshots/*.png

Search specific context

lancer search -t api_docs "authentication endpoints"

4. Set Appropriate Thresholds

Broad exploration:

lancer search --threshold 0.4 "general topic"

Precise matching:

lancer search --threshold 0.75 "specific concept"

Very high precision:

lancer search --threshold 0.85 -l 3 "exact information"

5. Use Filters for Structured Data

Combine semantic search with metadata

lancer search
--filter "status:eq:published"
--filter "category:eq:tutorial"
--threshold 0.6
"getting started guide"

6. Format Output for Scripting

JSON output for automation

lancer search --format json "query" | jq '.results[] | .path'

List tables programmatically

lancer tables list --format json | jq '.[] | .name'

MCP Server Mode

Running as MCP Server

Start MCP server for Claude Desktop integration

lancer mcp

With custom config

lancer mcp -c ~/.lancer/config.toml

With specific log level

lancer mcp --log-level info

Integration with Claude Desktop

Add to Claude Desktop config (~/Library/Application Support/Claude/claude_desktop_config.json ):

{ "mcpServers": { "lancer": { "command": "lancer", "args": ["mcp"] } } }

Performance Tips

1. Batch Operations

Ingest multiple files at once

lancer ingest file1.md file2.md file3.md

Use --stdin for large batches

find ./docs -name "*.md" | lancer ingest --stdin

2. Optimize Batch Size

Larger batches for bulk ingestion

lancer ingest --batch-size 500 ./large-corpus/

Smaller batches for limited memory

lancer ingest --batch-size 50 ./documents/

3. Skip Embeddings for Metadata-Only

Index metadata without generating embeddings

lancer ingest --no-embeddings ./archive/

4. Use Appropriate Models

Faster ingestion with smaller model

lancer ingest --text-model all-MiniLM-L6-v2 ./docs/

Better quality with larger model (slower)

lancer ingest --text-model bge-base-en-v1.5 ./docs/

Troubleshooting

Issue: Search returns no results

Solutions:

Lower the similarity threshold

lancer search --threshold 0.3 "query"

Check table exists and has documents

lancer tables list lancer tables info my_table

Try different search terms

lancer search "alternative phrasing"

Issue: Ingestion fails for some files

Solutions:

Check supported extensions

lancer ingest -e md,txt,pdf ./docs/

Set file size limits

lancer ingest --max-file-size 100000000 ./docs/

Use debug logging

lancer --log-level debug ingest document.pdf

Issue: Low search quality

Solutions:

Use better embedding model

lancer ingest --text-model bge-base-en-v1.5 document.md

Adjust chunk size

lancer ingest --chunk-size 1500 --chunk-overlap 300 document.md

Adjust search threshold

lancer search --threshold 0.6 "query"

Issue: Slow ingestion

Solutions:

Increase batch size

lancer ingest --batch-size 300 ./docs/

Use faster embedding model

lancer ingest --text-model all-MiniLM-L6-v2 ./docs/

Skip embeddings if not needed

lancer ingest --no-embeddings ./docs/

Quick Reference

Ingestion

lancer ingest document.md # Ingest single file lancer ingest -t docs ./directory/ # Ingest to specific table lancer ingest -e md,pdf ./docs/ # Filter by extensions lancer ingest --chunk-size 2000 document.md # Custom chunk size

Search

lancer search "query" # Search all tables lancer search -t docs "query" # Search specific table lancer search -l 20 "query" # Limit results lancer search --threshold 0.7 "query" # Set similarity threshold lancer search --filter "author:eq:John" "query" # Metadata filter

Table management

lancer tables list # List all tables lancer tables info my_table # Table information lancer tables delete old_table # Delete table

Configuration

lancer -c config.toml search "query" # Use config file lancer --log-level debug ingest doc.md # Set log level export LANCER_TABLE=docs # Set default table

MCP server

lancer mcp # Start MCP server

Common Patterns

Pattern 1: Quick Documentation Search

lancer search -t docs --threshold 0.7 -l 5 "how to configure authentication"

Pattern 2: Ingest and Test

lancer ingest -t test_docs document.md &&
lancer search -t test_docs "key concept from document"

Pattern 3: Find Similar Images

lancer search -t images --threshold 0.8 "sunset landscape photography"

Pattern 4: Batch Ingest with Verification

find ./docs -name "*.md" | lancer ingest -t docs --stdin &&
lancer tables info docs

Pattern 5: Precise Technical Search

lancer search -t technical_docs
--filter "language:eq:rust"
--threshold 0.75
-l 10
"async trait implementation patterns"

Summary

Primary use cases:

• Semantic search across documentation

• Multi-modal search (text and images)

• Knowledge base indexing and retrieval

• Integration with Claude via MCP

Key advantages:

• Semantic similarity (not just keyword matching)

• Multi-modal support (text and images)

• Flexible metadata filtering

• Multiple embedding model options

• Fast vector search with LanceDB

Most common commands:

• lancer ingest document.md

• Index documents

• lancer search "query"

• Search semantically

• lancer tables list

• Manage tables

• lancer search -t docs --threshold 0.7 "query"

• Precise search