{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_anuahesqgfbv","handle":"sekha-mcp","url":"https://wellknown.network/agents/sekha-mcp","links":{"self":"https://wellknown.network/agents/sekha-mcp/record.json","html":"https://wellknown.network/agents/sekha-mcp","markdown":"https://wellknown.network/agents/sekha-mcp/record.md","api":"https://wellknown.network/api/v1/agents/sekha-mcp","status":"https://wellknown.network/api/v1/agents/sekha-mcp/status","claim":"https://wellknown.network/agents/sekha-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/sekha-mcp/claim.json","badge":"https://wellknown.network/agents/sekha-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json"},"ard":{"identifier":"urn:air::server:sekha-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"sekha-mcp","summary":"Model Context Protocol server for Project Sekha - Persistent AI Memory Controller (v2.0 multi-provider compatible)","description":"# Sekha MCP Server\n\n> **Model Context Protocol Server for Sekha Memory**\n\n[![License: AGPL v3](https://img.shields.io/badge/License-AGPL%20v3-blue.svg)](https://www.gnu.org/licenses/agpl-3.0)\n[![CI Status](https://github.com/sekha-ai/sekha-mcp/actions/workflows/ci.yml/badge.svg)](https://github.com/sekha-ai/sekha-mcp/actions/workflows/ci.yml)\n[![codecov](https://codecov.io/gh/sekha-ai/sekha-mcp/branch/main/graph/badge.svg)](https://codecov.io/gh/sekha-ai/sekha-mcp)\n[![Python](https://img.shields.io/badge/python-3.11%2B-blue.svg)](https://www.python.org)\n[![PyPI](https://img.shields.io/pypi/v/sekha-mcp.svg)](https://pypi.org/project/sekha-mcp/)\n\n---\n\n## 🆕 v0.2.0 Release - Multi-Provider Support\n\n**Sekha MCP v0.2.0** is now compatible with the new Sekha v0.2.0 multi-provider architecture!\n\n**What's New:**\n- ✅ Works with Sekha v0.2.0 controller's multi-provider routing\n- ✅ Automatic provider fallback (Ollama, OpenAI, Anthropic, etc.)\n- ✅ Vision support (GPT-4o, Kimi 2.5) - just include images!\n- ✅ Cost-aware model selection\n- ✅ Multi-dimensional embeddings (per-dimension ChromaDB collections)\n- ✅ **Claude Desktop & Claude Code support** - memory in both apps!\n- ✅ **No API changes** - fully backward compatible!\n\n---\n\n## What is Sekha MCP?\n\nMCP (Model Context Protocol) server that exposes Sekha memory tools to any MCP-compatible client:\n\n- ✅ **Claude Desktop** - Anthropic's desktop app\n- ✅ **Claude Code** - VS Code extension (works with Ollama, Anthropic, or any provider)\n- ✅ **Any MCP client** - Standard protocol implementation\n\n**Supported Tools:**\n\n- ✅ `memory_store` - Save conversations\n- ✅ `memory_search` - Semantic search\n- ✅ `memory_get_context` - Retrieve relevant context\n- ✅ `memory_update` - Update conversation metadata\n- ✅ `memory_prune` - Get cleanup recommendations\n- ✅ `memory_export` - Export your data\n- ✅ `memory_stats` - View usage statistics\n\n**Total: 7 MCP tools**\n\n---\n\n## 📚 Documentation\n\n**Complete guide: [docs.sekha.dev/integrations/mcp](https://d…","publisher":null,"homepage":"https://docs.sekha.dev","repository":"https://github.com/sekha-ai/sekha-mcp/issues","version":"0.2.0","license":"AGPL-3.0-or-later","protocols":["mcp"],"tags":["ai","anthropic","chromadb","claude","claude-code","claude-desktop","context-management","conversation-memory","embeddings","mcp","memory","model-context-protocol","ollama","openai","rag","semantic-search","vector-database"],"pricing":null,"endpoints":[{"url":"pypi:sekha-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"data.vector-search","name":"Vector Search","confidence":1,"provenance":"declared"},{"slug":"knowledge.memory","name":"Agent Memory","confidence":1,"provenance":"declared"},{"slug":"data.database","name":"Databases","confidence":0.675,"provenance":"derived"}],"categories":["data","knowledge"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"sekha-mcp","registry":"pypi","observedAt":"2026-09-10T12:23:17.524Z","publishedAt":"2026-02-16T22:44:39.288906Z","latestVersion":"0.2.0"}},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"sekha-mcp","url":"https://pypi.org/project/sekha-mcp/","firstSeenAt":"2026-09-10T12:21:22.756Z","fetchedAt":"2026-09-10T12:21:22.756Z","normalizedAt":"2026-09-10T12:21:22.756Z"}]},"firstSeenAt":"2026-09-10T12:21:22.756Z","updatedAt":"2026-09-10T12:23:17.524Z"}