miminions.ai Use Cases
Discover how autonomous AI agents are transforming industries and workflows
miminions.ai empowers developers to create intelligent, autonomous agents that can handle complex tasks, maintain context, and integrate seamlessly with external tools. Explore real-world applications below.
Knowledge-Aware AI Agents
Build agents with long-term memory capabilities using vector databases like FAISS. Your agents can store, recall, and update knowledge dynamically, maintaining context across conversations.
- Store and retrieve knowledge efficiently
- Semantic search with similarity scoring
- Update and manage memory entries
- Context-aware responses
agent.store_knowledge(
"Python is a high-level programming language",
metadata={"category": "programming"}
)
Perfect For
- • Customer support agents that remember user history
- • Personal assistants with long-term context
- • Research agents that accumulate knowledge
- • Educational tutors with personalized learning
Intelligent Document Processing
Ingest and process documents (PDFs, text files) with automatic chunking for optimal retrieval. Agents can understand and query document content with semantic search.
- PDF and text file ingestion
- Automatic text chunking with overlap
- Semantic document search
- Metadata tagging and filtering
result = agent.execute_tool(
"ingest_document",
filepath="resume.pdf"
)
Perfect For
- • Legal document analysis and Q&A
- • Resume screening and candidate matching
- • Research paper summarization
- • Contract review and compliance
Model Context Protocol (MCP) Integration
Connect your agents to external tools and services using the Model Context Protocol. Dynamically load and execute tools from MCP servers alongside custom Python functions.
- Connect to MCP servers
- Load tools dynamically
- Mix MCP and local functions
- Async tool execution
await agent.connect_mcp_server(
"math_server", server_params
)
await agent.load_tools_from_mcp_server(
"math_server"
)
Perfect For
- • Workflow automation with external APIs
- • Data processing pipelines
- • Multi-tool agent orchestration
- • Integration with existing systems
SQLite Memory for Persistent Knowledge
Use SQLite-backed memory for permanent knowledge storage that persists across sessions. Perfect for agents that need to maintain state over time.
- Persistent storage across sessions
- CRUD operations on memory
- Custom database locations
- Metadata filtering and search
memory = SQLiteMemory(
db_path="agent_memory.db"
)
agent = create_simple_agent(
"PersistentAgent", memory=memory
)
Perfect For
- • Multi-session conversations
- • Knowledge base management
- • User preference tracking
- • Audit trails and logging
Ready to Build Your Own Agent?
Start creating autonomous AI agents with memory, tool integration, and document processing capabilities.