Place Fidelis in alphabetical order in memory catalog

README.md

@@ -2273,7 +2273,6 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [gpitrella/memxus-remote-mcp](https://github.com/gpitrella/memxus-remote-mcp) [![gpitrella/memxus-remote-mcp MCP server](https://glama.ai/mcp/servers/gpitrella/memxus-remote-mcp/badges/score.svg)](https://glama.ai/mcp/servers/gpitrella/memxus-remote-mcp) 📇 ☁️ - Shared context engine for devs and teams. Syncs GitHub, Notion, and saved decisions into reusable project context, so Claude, ChatGPT, Cursor, VS Code and Gemini start each session with the architecture and decisions the team already made. OAuth 2.1 PKCE, AES-256 encrypted, RFC 9728 compliant. `https://mcp.memxus.com/mcp`
 - [basemouse/basemouse-core](https://github.com/basemouse/basemouse-core) [![basemouse/basemouse-core MCP server](https://glama.ai/mcp/servers/basemouse/basemouse-core/badges/score.svg)](https://glama.ai/mcp/servers/basemouse/basemouse-core) 📇 ☁️ 🏠 - Shared, versioned memory for your agents across Claude Code, Cursor, Kiro and Grok. One MCP server, sourced answers, full history. Remote Streamable HTTP; anonymous browses a public demo corpus. Tools: `search`, `get_context_pack`, `upsert_document`. `https://basemouse.com/mcp`
 - [Fisher521/burn-mcp-server](https://github.com/Fisher521/burn-mcp-server) [![burn-mcp-server MCP server](https://glama.ai/mcp/servers/Fisher521/burn-mcp-server/badges/score.svg)](https://glama.ai/mcp/servers/Fisher521/burn-mcp-server) 📇 ☁️ 🍎 - Turn your read-later queue into an AI-accessible knowledge base. 26 tools to search, triage, and organize bookmarks saved in the Burn 451 app — the agent reads your inbox and decides what is worth keeping. `npx burn-mcp-server`
-- [hermes-labs-ai/fidelis](https://github.com/hermes-labs-ai/fidelis) [![hermes-labs-ai/fidelis MCP server](https://glama.ai/mcp/servers/hermes-labs-ai/fidelis/badges/score.svg)](https://glama.ai/mcp/servers/hermes-labs-ai/fidelis) 🐍 🏠 🍎 🐧 - Local-first memory for Codex, Claude Code, and other MCP clients. Four tools provide verbatim recall, query, health, and context-sensitive orientation through zero-LLM retrieval by default. Install `fidelis-memory` from PyPI, run `fidelis init`, then register the MCP server with the client.
 - [soolaugust/0CompactMem](https://github.com/soolaugust/0CompactMem) [![soolaugust/0CompactMem MCP server](https://glama.ai/mcp/servers/soolaugust/0CompactMem/badges/score.svg)](https://glama.ai/mcp/servers/soolaugust/0CompactMem) 🐍 🏠 🍎 🪟 🐧 - Persistent memory MCP server with OS-style demand paging, kswapd-style eviction, and mlock pinning. Multi-agent shared SQLite store with BM25 + FTS5 retrieval, importance scoring, and capacity-aware reclaim. 5 tools: `memory_lookup`, `pin_memory`, `unpin_memory`, `memory_stats`, `list_pinned`. `uvx --from git+https://github.com/soolaugust/0CompactMem memory-os`
 - [adelinamart/robrain](https://github.com/adelinamart/robrain) [![adelinamart/robrain MCP server](https://glama.ai/mcp/servers/adelinamart/robrain/badges/score.svg)](https://glama.ai/mcp/servers/adelinamart/robrain) 📇 🏠 🍎 🪟 🐧 - Self-hosted decision memory for AI coding agents. Passively captures architectural decisions with the alternatives you rejected (structured `rejected[]`), then warns the agent before it re-proposes a rejected approach. Postgres + pgvector; cross-tool across Claude Code, Cursor, Copilot, and Codex. Install: `npx robrain up && npx robrain install`.
 - [a2cr/a2cr](https://github.com/a2cr/a2cr) [![a2cr/a2cr MCP server](https://glama.ai/mcp/servers/a2cr/a2cr/badges/score.svg)](https://glama.ai/mcp/servers/a2cr/a2cr) 🐍 ☁️ 🏠 🍎 🪟 🐧 - MCP server for AI-agent handoffs. Saves client-encrypted WorkBaton checkpoints and WorkStash notes so Codex, Claude Code, Roo Code, and other MCP clients can resume work without passing full chat history.
@@ -2393,6 +2392,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
 - [harrison/ai-counsel](https://github.com/harrison/ai-counsel) - 🐍 🏠 🍎 🪟 🐧 - Deliberative consensus engine enabling multi-round debate between AI models with structured voting, convergence detection, and persistent decision graph memory.
 - [HBarefoot/engram](https://github.com/HBarefoot/engram) [![HBarefoot/engram MCP server](https://glama.ai/mcp/servers/HBarefoot/engram/badges/score.svg)](https://glama.ai/mcp/servers/HBarefoot/engram) 📇 🏠 🍎 🪟 🐧 - Local-first persistent memory for AI agents. SQLite + local embeddings (all-MiniLM-L6-v2), hybrid semantic + FTS5 recall, secret detection, and contradiction handling. 6 MCP tools (remember, recall, forget, feedback, context, status) over stdio. Zero cloud, no API keys, fully offline. Works with Claude Desktop/Code, Cursor, and Windsurf. `npm install -g @hbarefoot/engram`
 - [HatmanStack/ragstack-mcp](https://github.com/HatmanStack/RAGStack-Lambda/tree/main/src/ragstack-mcp) 🐍 ☁️ 🍎 🪟 🐧 - MCP server for RAGStack serverless knowledge bases. Search, chat with AI-generated answers, upload documents/media, scrape websites, and analyze metadata through an AWS-powered RAG pipeline (Lambda, Bedrock, S3, DynamoDB).
+- [hermes-labs-ai/fidelis](https://github.com/hermes-labs-ai/fidelis) [![hermes-labs-ai/fidelis MCP server](https://glama.ai/mcp/servers/hermes-labs-ai/fidelis/badges/score.svg)](https://glama.ai/mcp/servers/hermes-labs-ai/fidelis) 🐍 🏠 🍎 🐧 - Local-first memory for Codex, Claude Code, and other MCP clients. Four tools provide verbatim recall, query, health, and context-sensitive orientation through zero-LLM retrieval by default. Install `fidelis-memory` from PyPI, run `fidelis init`, then register the MCP server with the client.
 - [hifriendbot/cogmemai-mcp](https://github.com/hifriendbot/cogmemai-mcp) 📇 ☁️ 🍎 🪟 🐧 - Persistent cognitive memory for Claude Code. Cloud-first with semantic search, AI-powered extraction, and project scoping. Zero local databases.
 - [hjqcan/GoodMemory](https://github.com/hjqcan/GoodMemory) [![GoodMemory MCP server](https://glama.ai/mcp/servers/hjqcan/GoodMemory/badges/score.svg)](https://glama.ai/mcp/servers/hjqcan/GoodMemory) 📇 🏠 - Local-first, auditable memory layer for Codex, Claude Code, and MCP clients. Stores scoped user/project memory in SQLite or Postgres, exposes read-only recall, trace, stats, and artifact tools by default, and supports opt-in governed writeback with review, forget, and audit controls. Published as `io.github.hjqcan/goodmemory` in the official MCP Registry.
 - [hoornet/agentdocs-mcp](https://github.com/hoornet/agentdocs-mcp) [![hoornet/agentdocs-mcp MCP server](https://glama.ai/mcp/servers/hoornet/agentdocs-mcp/badges/score.svg)](https://glama.ai/mcp/servers/hoornet/agentdocs-mcp) 📇 ☁️ 🏠 🍎 🪟 🐧 - Read, search (full-text + pgvector semantic), create, update, comment on, and share AgentDocs (agentdocs.eu) Markdown docs — a collaborative docs platform with AI agents as first-class citizens. Local stdio (`npx -y agentdocs-mcp`) or hosted remote with OAuth 2.1 (`https://agentdocs.eu/mcp`), incl. slug-or-UUID addressing and space-scoped sandbox tokens.