mcp-lnav-canbus
A Model Context Protocol (MCP) server that exposes lnav log file analysis capabilities to AI assistants, specifically optimized for Kvaser Plain Text Log Frame CAN bus log processing.
README
MCP lnav CAN bus Server
A Model Context Protocol (MCP) server that exposes lnav log file analysis capabilities to AI assistants, specifically optimized for Kvaser Plain Text Log Frame CAN bus log processing.
Overview
This Python-based MCP server provides session-based access to CAN bus log files with structured JSON output, enabling AI models to analyze, query, and extract insights from Kvaser CAN bus logs through the Model Context Protocol.
Architecture
┌─────────────────────┐ ┌──────────────────────┐ ┌─────────────────┐
│ MCP Client │────▶│ MCP Server │────▶│ lnav CLI │
│ (Claude, Cursor) │◀────│ (Python, stdio) │◀────│ (v0.12.0+) │
└─────────────────────┘ └──────────────────────┘ └─────────────────┘
│
▼
┌──────────────────────┐
│ Session Manager │
│ (stateful context) │
└──────────────────────┘
│
▼
┌──────────────────────┐
│ Kvaser CAN Logs │
│ (.txt, .log) │
└──────────────────────┘
Requirements
Runtime Dependencies
- Python: 3.10 or higher
- lnav: 0.12.0 or higher (must be installed and available in PATH)
- MCP Python SDK: 2.0.0+ (v2 beta) or 1.27+ (v1 stable)
Supported Log Format
Primary Format: Kvaser Plain Text Log Frame
# Column format: Timestamp Channel Type Dir ID DLC Data
0.000000 0 Rx std 0x123 8 00 01 02 03 04 05 06 07
0.001000 0 Tx std 0x456 8 AA BB CC DD EE FF 00 11
Also Supported (via lnav auto-detection):
- Vector ASC
- CANalyzer TRC
- Generic CSV with timestamp/channel/id/data columns
Installation
1. Install lnav
# macOS
brew install lnav
# Ubuntu/Debian
sudo apt-get install lnav
# Or download from https://github.com/tstack/lnav/releases
Verify installation:
lnav --version
2. Install the MCP Server
# Using pip
pip install mcp-lnav-canbus
# Using uv
uv add mcp-lnav-canbus
Configuration
Claude Desktop
macOS: ~/Library/Application Support/Claude/claude_desktop_config.json
Linux: ~/.config/claude/claude_desktop_config.json
Windows: %APPDATA%\Claude\claude_desktop_config.json
{
"mcpServers": {
"lnav-canbus": {
"command": "python",
"args": ["-m", "mcp_lnav_canbus"],
"env": {
"LNAV_PATH": "/usr/local/bin/lnav"
}
}
}
}
Cursor
.cursor/mcp.json in project root:
{
"mcpServers": {
"lnav-canbus": {
"command": "python",
"args": ["-m", "mcp_lnav_canbus"],
"cwd": "/path/to/your/project",
"env": {
"LNAV_PATH": "/usr/local/bin/lnav"
}
}
}
}
VS Code (with MCP extension)
.vscode/mcp.json:
{
"servers": {
"lnav-canbus": {
"type": "stdio",
"command": "python",
"args": ["-m", "mcp_lnav_canbus"]
}
}
}
Tools
open_can_log
Open a Kvaser CAN bus log file in the current session.
Parameters:
file_path(string, required): Path to the Kvaser CAN log filesession_id(string, optional): Session identifier (auto-generated if not provided)
Example:
{
"name": "open_can_log",
"arguments": {
"file_path": "/data/can_trace.txt"
}
}
Response:
{
"success": true,
"session_id": "sess_abc123",
"file_info": {
"path": "/data/can_trace.txt",
"format": "kvaser",
"message_count": 15420,
"time_range": {
"start": "2024-01-15T10:00:00.000000",
"end": "2024-01-15T10:05:30.123456"
},
"channel_count": 2,
"unique_ids": 47
}
}
query_can_messages
Execute SQL queries against CAN bus log data using lnav's SQL engine.
Parameters:
query(string, required): SQLite query to executelimit(integer, optional, default: 100): Maximum rows to return
Example:
{
"name": "query_can_messages",
"arguments": {
"query": "SELECT can_id, COUNT(*) as count FROM log GROUP BY can_id ORDER BY count DESC LIMIT 10"
}
}
Response:
{
"success": true,
"columns": ["can_id", "count"],
"rows": [
["0x123", 1542],
["0x456", 987],
["0x789", 654]
],
"row_count": 3,
"execution_time_ms": 45
}
extract_can_frames
Extract specific CAN frames by ID, channel, or time range.
Parameters:
can_id(string, optional): CAN ID to filter (hex format, e.g., '0x123')channel(integer, optional): CAN channel number (0-based)start_time(string, optional): Start timestampend_time(string, optional): End timestamplimit(integer, optional, default: 1000): Maximum frames to return
Example:
{
"name": "extract_can_frames",
"arguments": {
"can_id": "0x123",
"start_time": "0.000000",
"end_time": "1.000000",
"limit": 100
}
}
Response:
{
"success": true,
"frames": [
{
"timestamp": "0.000000",
"channel": 0,
"type": "Rx",
"can_id": "0x123",
"dlc": 8,
"data": [0, 1, 2, 3, 4, 5, 6, 7]
}
],
"frame_count": 1,
"total_matching": 154
}
get_statistics
Generate statistical analysis of CAN bus traffic.
Parameters:
stat_type(string, required): "frequency", "timing", "load", "errors", or "summary"interval(string, optional): Time interval for aggregation (e.g., '1s', '100ms')can_id(string, optional): CAN ID to filter statistics
Example:
{
"name": "get_statistics",
"arguments": {
"stat_type": "frequency",
"interval": "1s"
}
}
Response:
{
"success": true,
"stat_type": "frequency",
"statistics": {
"by_id": [
{"can_id": "0x123", "count": 1542, "rate_hz": 100.0},
{"can_id": "0x456", "count": 987, "rate_hz": 64.2}
],
"total_messages": 15420,
"duration_seconds": 330.123456,
"average_rate_hz": 46.7
}
}
find_errors
Find error frames and anomalies in CAN bus logs.
Parameters:
error_type(string, optional, default: "all"): "all", "crc", "bit", "stuff", "form", "ack", "timeout", or "gap"channel(integer, optional): Channel filter
Example:
{
"name": "find_errors",
"arguments": {
"error_type": "crc"
}
}
Response:
{
"success": true,
"errors": [
{
"timestamp": "1.234567",
"channel": 0,
"error_type": "crc",
"can_id": "0x123",
"message": "CRC error detected"
}
],
"error_count": 1,
"error_rate_per_minute": 0.18
}
analyze_payload_noise
Analyze CAN bus payload repetition to detect noise in logs using MD5 hashes. This tool identifies repeated payloads that may represent noise or meaningless data in the log.
Parameters:
min_repetitions(integer, optional, default: 10): Minimum number of repetitions to consider as noisesession_id(string, optional): Session identifier
Example:
{
"name": "analyze_payload_noise",
"arguments": {
"min_repetitions": 5
}
}
Response:
{
"success": true,
"analysis": {
"total_frames": 1000,
"unique_payloads": 25,
"noise_patterns_found": 3,
"total_noisy_frames": 850,
"noise_percentage": 85.0,
"min_repetitions_threshold": 5
},
"noise_patterns": [
{
"payload_md5": "0ee0646c1c77d8131cc8f4ee65c7673b",
"repetition_count": 500,
"payload_hex": "01 02 03 04 05 06 07 08",
"first_timestamp": "0.000000",
"last_timestamp": "10.500000",
"time_span_seconds": 10.5,
"can_ids": ["0x123"],
"channels": [0],
"noise_ratio": 0.5
}
]
}
scan_payload_for_value
Scan CAN bus payload bytes for a specific decimal value. Searches for frames where consecutive bytes in the payload match the binary representation of the given decimal value. Supports both big-endian and little-endian byte orders.
Parameters:
byte_value(integer, required): Decimal value to search for (0 to unlimited, auto-calculates byte width)endianness(string, optional, default: "big"): Byte order ("big" or "little")start_offset(integer, optional, default: 0): Start searching from this byte offsetend_offset(integer, optional, default: None): Stop searching at this byte offset (None searches to end)limit(integer, optional, default: 1000): Maximum frames to returnsession_id(string, optional): Session identifier
Example:
{
"name": "scan_payload_for_value",
"arguments": {
"byte_value": 65535,
"endianness": "big",
"limit": 10
}
}
Response:
{
"success": true,
"search_criteria": {
"byte_value": 65535,
"endianness": "big",
"start_offset": 0,
"end_offset": null,
"byte_width": 2,
"target_bytes_hex": "FF FF"
},
"matches": [
{
"timestamp": "0.001000",
"channel": 0,
"type": "Tx",
"direction": "std",
"can_id": "0x456",
"dlc": 8,
"data": [170, 187, 255, 255, 238, 239, 0, 17],
"payload_hex": "AA BB FF FF EE EF 00 11",
"match_position": 2,
"match_bytes": [255, 255],
"byte_width": 2
}
],
"match_count": 1,
"frames_scanned": 10,
"frames_skipped_too_short": 0
}
Use Cases:
- Find frames containing specific sensor values (e.g., temperature = 255)
- Search for error codes encoded in payload bytes
- Locate frames with specific multi-byte values (e.g., 16-bit counters, 32-bit timestamps)
- Debug communication issues by finding frames with unexpected byte patterns
get_session_info
Retrieve information about the current session state.
Parameters: None
Response:
{
"success": true,
"session_id": "sess_abc123",
"files_loaded": [
{
"path": "/data/can_trace.txt",
"format": "kvaser",
"message_count": 15420,
"loaded_at": "2024-01-15T14:30:00Z"
}
],
"active_filters": [],
"lnav_version": "0.12.0",
"session_duration_seconds": 120
}
close_session
Close the current session and release resources.
Parameters: None
Response:
{
"success": true,
"session_id": "sess_abc123",
"message": "Session closed successfully"
}
Resources
The server provides the following MCP resources:
canbus://session/{session_id}/log
Access the current session's loaded log file content.
Example URI: canbus://session/sess_abc123/log
canbus://session/{session_id}/messages/{can_id}
Access specific CAN ID messages from the session.
Example URI: canbus://session/sess_abc123/messages/0x123
canbus://session/{session_id}/errors
Access error frames from the session's log file.
Example URI: canbus://session/sess_abc123/errors
Prompts
canbus-analyze
Generate a comprehensive analysis of a Kvaser CAN bus log file.
Parameters:
file_path(string, required): Path to the Kvaser CAN log fileanalysis_type(string, optional): "quick", "detailed", "errors", "traffic", or "custom" (default: "detailed")focus_ids(array, optional): List of CAN IDs to focus analysis on
Example:
/canbus-analyze file_path="/data/can_trace.txt" analysis_type="detailed"
canbus-decode-frame
Help decode and interpret a specific CAN frame.
Parameters:
can_id(string, required): CAN ID to decodedata_bytes(array, required): Data bytes to decodedbc_file(string, optional): Path to DBC file for signal decoding
Example:
/canbus-decode-frame can_id="0x123" data_bytes=[0,1,2,3,4,5,6,7]
Session Lifecycle
Session Creation
- Client initiates MCP connection via stdio
- Server creates session context with unique session ID
- Server spawns lnav process for the session
- Session state initialized (empty file list, no filters)
Session Usage
- Client calls
open_can_logto load a file - Server loads file into lnav, updates session state
- Client makes queries using session context
- Server maintains lnav process and state between calls
Session Termination
- Client calls
close_sessionor disconnects - Server terminates lnav process
- Server releases session resources
- Session state cleared
Server Configuration
Transport
Transport Protocol: stdio only
The server communicates via standard input/output streams, suitable for local CLI integration and subprocess spawning.
Session Management
The server maintains session-based state between calls:
- Each client connection establishes a session context
- Session persists for the lifetime of the MCP connection
- Loaded files remain in session memory for subsequent queries
- Session state includes: loaded files, active filters, query history, lnav process handle
Path Validation
Pass-through to lnav: The server does not validate file paths. Path validation and error handling is delegated to lnav, which returns appropriate error messages for invalid paths.
Environment Variables
| Variable | Description | Default |
|---|---|---|
LNAV_PATH |
Path to lnav binary | lnav (from PATH) |
LNAV_TIMEOUT |
Default timeout for lnav operations (seconds) | 30 |
MAX_SESSION_COUNT |
Maximum concurrent sessions | 10 |
LOG_LEVEL |
Logging verbosity | INFO |
Server Startup
# Basic usage
python -m mcp_lnav_canbus
# With custom lnav path
LNAV_PATH=/usr/local/bin/lnav python -m mcp_lnav_canbus
# With debug logging
LOG_LEVEL=DEBUG python -m mcp_lnav_canbus
Error Handling
Error Response Format
{
"success": false,
"error": {
"code": "FILE_NOT_FOUND",
"message": "File not found: /path/to/log.txt",
"details": {
"path": "/path/to/log.txt",
"lnav_error": "Unable to open file"
}
}
}
Error Codes
| Code | Description |
|---|---|
FILE_NOT_FOUND |
Specified file path does not exist |
INVALID_FORMAT |
Log file format not recognized |
QUERY_ERROR |
SQL query syntax error |
SESSION_ERROR |
Session not found or expired |
LNAV_ERROR |
lnav process error |
TIMEOUT |
Operation timed out |
INTERNAL_ERROR |
Internal server error |
Usage Examples
Example 1: Basic Log Analysis
// Request
{
"tool": "open_can_log",
"arguments": {
"file_path": "/data/can_trace.txt"
}
}
// Response
{
"success": true,
"session_id": "sess_abc123",
"file_info": {
"path": "/data/can_trace.txt",
"format": "kvaser",
"message_count": 15420,
"time_range": {
"start": "2024-01-15T10:00:00.000000",
"end": "2024-01-15T10:05:30.123456"
},
"channel_count": 2,
"unique_ids": 47
}
}
Example 2: Query by CAN ID
// Request
{
"tool": "query_can_messages",
"arguments": {
"query": "SELECT can_id, COUNT(*) as count FROM log GROUP BY can_id ORDER BY count DESC LIMIT 10"
}
}
// Response
{
"success": true,
"columns": ["can_id", "count"],
"rows": [
["0x123", 1542],
["0x456", 987],
["0x789", 654]
],
"row_count": 3
}
Example 3: Error Detection
// Request
{
"tool": "find_errors",
"arguments": {
"error_type": "all"
}
}
// Response
{
"success": true,
"errors": [
{
"timestamp": "1.234567",
"channel": 0,
"error_type": "crc",
"can_id": "0x123",
"message": "CRC error detected"
}
],
"error_count": 1,
"error_rate_per_minute": 0.18
}
Security Considerations
- Server runs with same permissions as host process
- File access limited to paths provided in tool calls
- No network access performed (stdio transport only)
- SQL queries executed in sandboxed lnav session
- Session isolation prevents cross-session data access
- Command injection prevented via parameterized queries
Troubleshooting
Common Issues
lnav not found:
Error: LNAV_PATH not set or lnav not in PATH
Solution: Set LNAV_PATH environment variable or install lnav
Invalid log format:
Error: INVALID_FORMAT
Solution: Ensure log file is Kvaser Plain Text Log Frame format
Session timeout:
Error: SESSION_ERROR
Solution: Check session_id is valid and session hasn't expired
Query syntax error:
Error: QUERY_ERROR
Solution: Verify SQLite syntax in query parameter
Performance Considerations
- Large log files indexed on open (progress reported to client)
- SQL queries executed via lnav's SQLite integration
- Result limiting prevents memory exhaustion
- Timeout enforcement prevents hung operations
Limitations
- Binary formats (BLF, MF4) require external conversion tools
- Real-time log tailing is not supported (batch processing only)
- DBC signal decoding requires external DBC parser integration
- Maximum file size recommendations apply for performance
Development
Running in Development Mode
Use the MCP Inspector to test the server:
uv run mcp dev server.py
Testing
# Run tests
pytest tests/
# Run with coverage
pytest --cov=mcp_lnav_canbus tests/
Version Compatibility
| Component | Minimum Version | Recommended Version |
|---|---|---|
| Python | 3.10 | 3.11+ |
| lnav | 0.12.0 | 0.14.0+ |
| MCP SDK | 1.27.0 or 2.0.0b1 | 2.0.0b1+ |
Contributing
Contributions are welcome! Please see our Contributing Guide for details.
License
This project is licensed under the MIT License - see the LICENSE file for details.
Acknowledgments
- lnav - Log File Navigator by Timothy Stack
- Model Context Protocol - MCP specification
- MCP Python SDK - Python implementation
Resources
Recommended Servers
playwright-mcp
A Model Context Protocol server that enables LLMs to interact with web pages through structured accessibility snapshots without requiring vision models or screenshots.
Magic Component Platform (MCP)
An AI-powered tool that generates modern UI components from natural language descriptions, integrating with popular IDEs to streamline UI development workflow.
Audiense Insights MCP Server
Enables interaction with Audiense Insights accounts via the Model Context Protocol, facilitating the extraction and analysis of marketing insights and audience data including demographics, behavior, and influencer engagement.
VeyraX MCP
Single MCP tool to connect all your favorite tools: Gmail, Calendar and 40 more.
graphlit-mcp-server
The Model Context Protocol (MCP) Server enables integration between MCP clients and the Graphlit service. Ingest anything from Slack to Gmail to podcast feeds, in addition to web crawling, into a Graphlit project - and then retrieve relevant contents from the MCP client.
Kagi MCP Server
An MCP server that integrates Kagi search capabilities with Claude AI, enabling Claude to perform real-time web searches when answering questions that require up-to-date information.
E2B
Using MCP to run code via e2b.
Neon Database
MCP server for interacting with Neon Management API and databases
Exa Search
A Model Context Protocol (MCP) server lets AI assistants like Claude use the Exa AI Search API for web searches. This setup allows AI models to get real-time web information in a safe and controlled way.
Qdrant Server
This repository is an example of how to create a MCP server for Qdrant, a vector search engine.