Use Case: AI Self-Configuring MCP Servers at Runtime

The Problem

You don't always know upfront which tools a session will need. A developer asks "help me with the GitHub issues" but the GitHub MCP server isn't configured. Or the AI realizes mid-task it needs a database tool. Traditionally, you'd stop, edit config, restart. Octomind lets the AI handle this itself.

Solution

The built-in mcp tool lets the AI add, enable, and remove MCP servers during a live session.

How It Works

The AI can manage its own tool ecosystem at runtime:

User: "Check the open GitHub issues for this repo"

AI (thinking): "I don't have GitHub tools. Let me add the GitHub MCP server."

AI calls: mcp(action="add", name="github", server_type="http",
          url="https://api.github.com/mcp", timeout_seconds=30)

AI calls: mcp(action="enable", name="github")

AI: "Connected to GitHub MCP server. Found 12 open issues..."

No config changes. No restart. The AI recognized a gap and filled it.

Example: Full Dynamic Tool Discovery

User: "I need to analyze our database schema and cross-reference with GitHub issues"

AI:
  1. mcp(action="list")
     -> Shows: core (builtin), filesystem (stdio) -- no GitHub, no DB tools

  2. mcp(action="add", name="github", server_type="http",
         url="https://api.github.com/mcp", timeout_seconds=30)
     -> "Server 'github' registered"

  3. mcp(action="enable", name="github")
     -> "Server 'github' enabled. Available tools: github_list_issues, github_search_code, ..."

  4. mcp(action="add", name="db", server_type="stdio",
         command="mcp-postgres", args=["--connection", "postgresql://..."])
     -> "Server 'db' registered"

  5. mcp(action="enable", name="db")
     -> "Server 'db' enabled. Available tools: query, list_tables, describe_table, ..."

  6. Now uses both servers to cross-reference issues with schema

  7. When done:
     mcp(action="disable", name="db")  # Clean up sensitive connection

Persisting Dynamic Servers

If a dynamically added server proves useful, persist it to config:

AI calls: mcp(action="persist", name="github")
-> Saved to ~/.local/share/octomind/config/mcp-github.toml
-> Auto-binds to current role for future sessions

Remove persisted config:

AI calls: mcp(action="unpersist", name="github")
-> Removed from config directory

Stdio Servers (Local Tools)

The AI can spin up local tool servers too:

AI calls: mcp(action="add", name="octocode", server_type="stdio",
          command="octocode", args=["mcp", "--path=."], timeout_seconds=240)

AI calls: mcp(action="enable", name="octocode")
-> "Server 'octocode' enabled. Available tools: semantic_search, view_signatures, graphrag"

Tool Filtering

Only expose specific tools from a server:

AI calls: mcp(action="add", name="github", server_type="http",
          url="https://api.github.com/mcp",
          tools=["github_list_issues", "github_create_issue"])

Or use wildcards:

tools=["github_*"]

Dynamic Agents Too

The same pattern works for agents. The AI can create specialized agents at runtime:

AI calls: agent(action="add", name="db_expert",
           description="Analyzes database schemas and queries",
           system="You are a database expert...",
           server_refs=["filesystem", "db"],
           allowed_tools=["filesystem:view", "db:*"])

AI calls: agent(action="enable", name="db_expert")

AI calls: agent_db_expert(task="Analyze the schema for N+1 query risks")

Practical Scenario: Self-Assembling Toolkit

Prompt the AI to assess what it needs:

User: "You have access to the filesystem. Before you start working on this project,
       check what tools would be useful and set them up."

AI:
  1. Reads project files: package.json, Cargo.toml, docker-compose.yml
  2. Discovers: Rust project with PostgreSQL, uses GitHub for issues
  3. Sets up:
     - octocode (code search)
     - postgres MCP (database)
     - github MCP (issues/PRs)
  4. Reports: "I've connected 3 additional tool servers. Ready to work."

MCP Management Commands

Action	Description
list	Show all servers with status
add	Register new server (doesn't connect)
enable	Connect and activate tools
disable	Deactivate (keep config)
remove	Unregister entirely
persist	Save to config for future sessions
unpersist	Remove from saved config

Session command equivalent: /mcp list, /mcp add ..., etc.

Key Points

• The AI can add/remove MCP servers without human intervention
• Supports both HTTP (remote) and stdio (local process) servers
• persist saves a dynamic server to config for future sessions
• Tool filtering prevents exposing unnecessary capabilities
• Dynamic agents follow the same add/enable/disable/remove pattern
• This is unique to Octomind -- most AI tools require static tool configuration
• The AI can assess a project and self-configure its toolkit