Agentic Workflows and MCP
Definition
Agentic workflows are multi-step AI processes where an LLM takes autonomous actions — reading files, querying tools, writing outputs — to complete a goal. MCP (Model Context Protocol) is an open protocol that standardizes how agents connect to external tools and data sources.
The MCP Protocol
MCP decouples agents from specific tool implementations:
- Agents speak a common protocol
- Tool providers (memory systems, databases, APIs) implement MCP servers
- Any MCP-compatible agent can use any MCP-compatible tool without custom integration code
Supported in: Claude (Anthropic), Cursor, VS Code Copilot, Codex, and others.
A Standard Agent Contract (from Link)
The Link project defines a minimal four-step protocol that well-behaved agents should follow when using memory:
- Check status — confirm memory is available and up to date
- Ingest sources — add new raw material to the knowledge base
- Query context — retrieve relevant knowledge before responding
- Validate changes — confirm that updates were applied correctly
This pattern generalizes beyond memory: it’s a sound contract for any agent interacting with stateful external systems.
Agentic Workflow Patterns
| Pattern | Description |
|---|---|
| Check → Act → Validate | Read state, make change, confirm result |
| Ingest → Index → Query | Process source, update catalog, retrieve on demand |
| Observe → Plan → Execute | Perceive environment, form plan, run steps |