# MCP Server Configuration for Agentforce Vibes
## Your Log Analyzer MCP Server Configuration
Add this to your Agentforce Vibes remote MCP servers:
```json
{
"name": "Log Analyzer FAISS",
"description": "Local FAISS-powered log analysis with semantic search, error detection, and pattern clustering. 100% local, no cloud APIs, 30-150x faster than traditional search.",
"url": "git+https://github.com/suriya-ML/log-checker-mcp.git",
"type": "uvx",
"config": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/suriya-ML/log-checker-mcp.git",
"log-analyzer-mcp"
],
"env": {
"LOG_FOLDER": "/path/to/logs"
}
},
"tools": [
{
"name": "fetch_local_logs",
"description": "Fetch and chunk local log files with configurable size and overlap",
"parameters": {
"input_folder": "Path to folder containing log files (optional)",
"chunk_size": "Size of each chunk in characters (default: 4096)",
"overlap": "Overlap between chunks in characters (default: 1024)"
}
},
{
"name": "store_chunks_as_vectors",
"description": "Vectorize log chunks with local embeddings and build FAISS index for fast similarity search",
"parameters": {
"use_cache": "Whether to use embedding cache (default: true)",
"clear_cache": "Whether to clear cache before starting (default: false)"
}
},
{
"name": "query_SFlogs",
"description": "Query vectorized logs with semantic search, hybrid retrieval, and intelligent error analysis",
"parameters": {
"query": "Natural language query to search logs (required)"
}
}
],
"features": [
"Semantic log search with FAISS",
"30-150x faster than traditional search",
"Intelligent error pattern detection",
"Local sentence-transformers embeddings",
"Smart caching for instant re-indexing",
"Hybrid semantic + lexical retrieval",
"No cloud APIs required",
"Zero cost operation"
],
"requirements": {
"python": ">=3.9",
"packages": [
"mcp>=0.9.0",
"sentence-transformers>=2.2.0",
"numpy>=1.24.0",
"faiss-cpu>=1.7.4",
"torch>=2.0.0"
]
}
}
```
## Compact Version (Minimal)
```json
{
"name": "Log Analyzer FAISS",
"url": "git+https://github.com/suriya-ML/log-checker-mcp.git",
"command": "uvx",
"args": ["--from", "git+https://github.com/suriya-ML/log-checker-mcp.git", "log-analyzer-mcp"]
}
```
## For Python-based Remote MCP Configuration
```python
mcp_server = {
"name": "log-analyzer-faiss",
"repository": "https://github.com/suriya-ML/log-checker-mcp.git",
"type": "git",
"runner": "uvx",
"description": "FAISS-powered log analysis with semantic search",
"tools": ["fetch_local_logs", "store_chunks_as_vectors", "query_SFlogs"],
"env": {
"LOG_FOLDER": "/default/log/path"
}
}
```
## For REST API Configuration
```json
{
"mcpServer": {
"id": "log-analyzer-faiss",
"name": "Log Analyzer FAISS",
"repository": "https://github.com/suriya-ML/log-checker-mcp.git",
"branch": "main",
"type": "uvx",
"enabled": true,
"autoUpdate": true,
"config": {
"env": {
"LOG_FOLDER": "${USER_LOG_FOLDER}"
}
},
"capabilities": {
"tools": true,
"resources": false,
"prompts": false
}
}
}
```
## For YAML Configuration
```yaml
name: log-analyzer-faiss
description: Local FAISS-powered log analysis with semantic search
repository: https://github.com/suriya-ML/log-checker-mcp.git
type: uvx
runner:
command: uvx
args:
- --from
- git+https://github.com/suriya-ML/log-checker-mcp.git
- log-analyzer-mcp
environment:
LOG_FOLDER: /path/to/logs
tools:
- name: fetch_local_logs
description: Fetch and chunk local log files
- name: store_chunks_as_vectors
description: Vectorize logs with FAISS indexing
- name: query_SFlogs
description: Semantic log search with error analysis
features:
- semantic_search
- faiss_indexing
- error_detection
- local_processing
- zero_cost
```
## For Agentforce Registry Format
```json
{
"serverDefinition": {
"identifier": "suriya-ML/log-checker-mcp",
"displayName": "Log Analyzer FAISS",
"description": "Local FAISS-powered log analysis with semantic search, error detection, and pattern clustering. 30-150x faster than traditional search.",
"category": "analytics",
"tags": ["logs", "faiss", "semantic-search", "error-detection", "local"],
"author": "suriya-ML",
"license": "MIT",
"repository": {
"type": "github",
"url": "https://github.com/suriya-ML/log-checker-mcp"
},
"installation": {
"type": "uvx",
"package": "git+https://github.com/suriya-ML/log-checker-mcp.git"
},
"runtime": {
"type": "python",
"minVersion": "3.9"
},
"configuration": {
"required": [],
"optional": [
{
"name": "LOG_FOLDER",
"type": "string",
"description": "Path to log files directory",
"default": "./logs"
},
{
"name": "EMBED_MODEL",
"type": "string",
"description": "Sentence-transformers model name",
"default": "all-MiniLM-L6-v2"
},
{
"name": "FAISS_INDEX_TYPE",
"type": "string",
"description": "FAISS index type",
"default": "IVFFlat",
"enum": ["Flat", "IVFFlat", "IVFPQ", "HNSW"]
}
]
},
"tools": [
{
"name": "fetch_local_logs",
"description": "Fetch and chunk local log files with configurable chunk size and overlap",
"inputSchema": {
"type": "object",
"properties": {
"input_folder": {
"type": "string",
"description": "Path to folder containing log files"
},
"chunk_size": {
"type": "integer",
"description": "Size of each chunk in characters",
"default": 4096
},
"overlap": {
"type": "integer",
"description": "Overlap between chunks in characters",
"default": 1024
}
}
}
},
{
"name": "store_chunks_as_vectors",
"description": "Vectorize log chunks with local embeddings and build FAISS index",
"inputSchema": {
"type": "object",
"properties": {
"use_cache": {
"type": "boolean",
"description": "Whether to use embedding cache",
"default": true
},
"clear_cache": {
"type": "boolean",
"description": "Whether to clear cache before starting",
"default": false
}
}
}
},
{
"name": "query_SFlogs",
"description": "Query vectorized logs with semantic search and error analysis",
"inputSchema": {
"type": "object",
"properties": {
"query": {
"type": "string",
"description": "Natural language query to search logs"
}
},
"required": ["query"]
}
}
],
"metrics": {
"performance": "30-150x faster than traditional search",
"cost": "$0 (100% local)",
"privacy": "Complete (no cloud APIs)"
}
}
}
```
## Quick Copy-Paste for Most Systems
```json
{
"name": "log-analyzer-faiss",
"url": "git+https://github.com/suriya-ML/log-checker-mcp.git",
"type": "uvx",
"description": "FAISS-powered log analysis with semantic search"
}
```
## Environment Variables (Optional)
```bash
LOG_FOLDER=/path/to/logs
EMBED_MODEL=all-MiniLM-L6-v2
FAISS_INDEX_TYPE=IVFFlat
FAISS_NLIST=100
FAISS_NPROBE=10
FAISS_TOP_K=150
```
Choose the format that matches your Agentforce Vibes configuration system!
