Model Context Protocol server for Project Sekha - Persistent AI Memory Controller (v2.0 multi-provider compatible)
Wellknown found it in public sources; nobody has proven control of it yet. Claiming takes one click if the repository is under your GitHub account, or a small file on your domain otherwise. Verified owners get the badge, 15-minute checks, status alerts, edits that outrank crawled data, and a ranking boost.
Agents can do it too: POST https://wellknown.network/api/v1/claims with {"agent":"sekha-mcp","method":"well_known_file"} — machine-readable steps at claim.json, guide at /docs/claim.
Everything here was measured by our prober or read from a registry. Nothing is self-reported.
Attributed to the source that supplied each field. Treated as claims, not facts.
# Sekha MCP Server > **Model Context Protocol Server for Sekha Memory** [](https://www.gnu.org/licenses/agpl-3.0) [](https://github.com/sekha-ai/sekha-mcp/actions/workflows/ci.yml) [](https://codecov.io/gh/sekha-ai/sekha-mcp) [](https://www.python.org) [](https://pypi.org/project/sekha-mcp/) --- ## 🆕 v0.2.0 Release - Multi-Provider Support **Sekha MCP v0.2.0** is now compatible with the new Sekha v0.2.0 multi-provider architecture! **What's New:** - ✅ Works with Sekha v0.2.0 controller's multi-provider routing - ✅ Automatic provider fallback (Ollama, OpenAI, Anthropic, etc.) - ✅ Vision support (GPT-4o, Kimi 2.5) - just include images! - ✅ Cost-aware model selection - ✅ Multi-dimensional embeddings (per-dimension ChromaDB collections) - ✅ **Claude Desktop & Claude Code support** - memory in both apps! - ✅ **No API changes** - fully backward compatible! --- ## What is Sekha MCP? MCP (Model Context Protocol) server that exposes Sekha memory tools to any MCP-compatible client: - ✅ **Claude Desktop** - Anthropic's desktop app - ✅ **Claude Code** - VS Code extension (works with Ollama, Anthropic, or any provider) - ✅ **Any MCP client** - Standard protocol implementation **Supported Tools:** - ✅ `memory_store` - Save conversations - ✅ `memory_search` - Semantic search - ✅ `memory_get_context` - Retrieve relevant context - ✅ `memory_update` - Update conversation metadata - ✅ `memory_prune` - Get cleanup recommendations - ✅ `memory_export` - Export your data - ✅ `memory_stats` - View usage statistics **Total: 7 MCP tools** --- ## 📚 Documentation **Complete guide: [docs.sekha.dev/integrations/mcp](https://d…
Mapped onto the structured taxonomy from declared text and observed tool names. Confidence shown for derived entries.
Every source is kept verbatim. Field changes are logged as events.