feat(mcp): expose taxonomy browsing + tiered search as an MCP server

[sebastianbraun25]

Problem

list_taxonomy_items/get_taxonomy_item/TieredWikiSearch (#258/#259) and their CLI
exposure (openkb list-taxonomy/openkb search, #260/#261) require either running inside
the OpenKB Python process or shelling out to the openkb CLI. Modern AI coding assistants
(GitHub Copilot, Claude Code, Cursor, etc.) increasingly support the Model Context Protocol
(MCP) as their preferred way to call structured, typed tools — an MCP server would let any
MCP-capable assistant browse the taxonomy and run the tiered search directly, without
needing a CLI wrapper, shell access, or Node.js/the Workbench web UI.

Kontext

• mcp==1.27.1 is already an installed, resolved dependency — transitively, via
  openai-agents (see PR chore: bump openai-agents to 0.19.0 and openai to 2.48.0 #207, which bumped openai-agents for MCP Python SDK v2 client
  support: MCPServerStdio/MCPServerStreamableHttp). It already provides
  mcp.server.fastmcp.FastMCP, a minimal decorator-based MCP server API. This issue is
  therefore not proposing a new dependency, just an explicit top-level pin
  (pyproject.toml) formalizing what's already vetted and present, plus a small new module
  using it.

Vorschlag

• New module (e.g. openkb/mcp_server.py) exposing list_taxonomy and search_wiki as
  MCP tools, built on the same core functions the CLI/agent already use
  (agent.tools.list_taxonomy_items/get_taxonomy_item, fulltext_index.TieredWikiSearch).
• No index cache: the underlying index is rebuilt fresh on every tool call, exactly like
  the CLI and agent do today — deliberately, since OpenKB has no long-running daemon
  concept today and caching would risk staleness if the KB changes in a separate openkb add invocation while the MCP server process stays alive.
• New CLI entry point (e.g. openkb-mcp) in pyproject.toml to launch the server (stdio
  transport) for use from an MCP-capable client's config.

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_{This issue was drafted with the assistance of an AI assistant.}