From 6ec010dba6f632d889dccdb2958c090d693ff22f Mon Sep 17 00:00:00 2001 From: Sean Markwei Date: Sun, 5 Jul 2026 06:27:37 +0000 Subject: [PATCH 1/2] Add seanmarkwei/agentram-mcp to Memory Persistent key-value memory for AI agents, no vector DB. Published on npm. --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 5b03c3aeb..9e3bf9943 100644 --- a/README.md +++ b/README.md @@ -2089,6 +2089,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to - [roomi-fields/notebooklm-mcp](https://github.com/roomi-fields/notebooklm-mcp) [![notebooklm-mcp MCP server](https://glama.ai/mcp/servers/@roomi-fields/notebooklm-mcp/badges/score.svg)](https://glama.ai/mcp/servers/@roomi-fields/notebooklm-mcp) 📇 🏠 🍎 🪟 🐧 - Full automation of Google NotebookLM — Q&A with citations, audio podcasts, video, content generation, source management, and notebook library. MCP + HTTP REST API. - [rushikeshmore/CodeCortex](https://github.com/rushikeshmore/CodeCortex) [![codecortex MCP server](https://glama.ai/mcp/servers/@rushikeshmore/codecortex/badges/score.svg)](https://glama.ai/mcp/servers/@rushikeshmore/codecortex) 📇 🏠 🍎 🪟 🐧 - Persistent codebase knowledge layer for AI coding agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) via tree-sitter native parsing (28 languages) and serves via MCP. 14 tools, ~85% token reduction. Works with Claude Code, Cursor, Codex, and any MCP client. - [s60yucca/mnemos](https://github.com/s60yucca/mnemos) [![s60yucca/mnemos MCP server](https://glama.ai/mcp/servers/s60yucca/mnemos/badges/score.svg)](https://glama.ai/mcp/servers/s60yucca/mnemos) 🏎️ 🏠 🍎 🪟 🐧 - Persistent memory engine for AI coding agents. Stores architecture decisions, bug root causes, and project conventions across sessions. Single Go binary with embedded SQLite, FTS5 search, context assembly within token budgets, and autopilot setup for Claude Code, Kiro, and Cursor. +- [seanmarkwei/agentram-mcp](https://github.com/seanmarkwei/agentram-mcp) 📇 ☁️ - Persistent memory for AI agents through a simple key-value HTTP API. No vector database or embeddings required. Store, retrieve, search, and share memory across agents with shared namespaces and TTL support. `npx -y agentram-mcp` - [SagaPeak/artifacta-mcp](https://github.com/SagaPeak/artifacta-mcp) [![SagaPeak/artifacta-mcp MCP server](https://glama.ai/mcp/servers/SagaPeak/artifacta-mcp/badges/score.svg)](https://glama.ai/mcp/servers/SagaPeak/artifacta-mcp) 🎖️ 📇 🐍 ☁️ 🍎 🪟 🐧 - The artifact store for AI agents. Every output your agents produce — persisted, retrievable, shareable. Across runs, sessions, and tools. Session/agent metadata, content-hash dedup, expiring share links; 11 tools with path-confined uploads and destructive actions gated by default. TypeScript (`npx @artifacta-mcp/mcp`) and Python (`pipx run artifacta-mcp`). - [SaravananJaichandar/world-model-mcp](https://github.com/SaravananJaichandar/world-model-mcp) [![SaravananJaichandar/world-model-mcp MCP server](https://glama.ai/mcp/servers/SaravananJaichandar/world-model-mcp/badges/score.svg)](https://glama.ai/mcp/servers/SaravananJaichandar/world-model-mcp) 🐍 🏠 🍎 🪟 🐧 - Temporal knowledge graph for codebases. Captures decision traces, links test failures to code changes, learns co-edit patterns, predicts regression risk, and enforces learned constraints at the edit boundary via a PreToolUse hook. 22 MCP tools, 9 SQLite databases with FTS5, supports Python/TypeScript/JavaScript/Solidity/Go/Rust/Java. Install via `pip install world-model-mcp`. - [sachitrafa/YourMemory](https://github.com/sachitrafa/YourMemory) [![sachitrafa/YourMemory MCP server](https://glama.ai/mcp/servers/sachitrafa/YourMemory/badges/score.svg)](https://glama.ai/mcp/servers/sachitrafa/YourMemory) 🐍 🏠 🍎 🪟 🐧 - Persistent memory for AI agents with Ebbinghaus forgetting-curve decay, hybrid BM25+vector retrieval, and entity graph for multi-hop reasoning. Memories auto-prune by importance and recall rate. Built-in browser dashboard, multi-agent support, and `yourmemory ask` for zero-API-call local queries. `pip install yourmemory` From 507e5aee5bb6ca9cd49a9ff34141656871bdd7e3 Mon Sep 17 00:00:00 2001 From: Sean Markwei Date: Wed, 15 Jul 2026 05:55:46 +0000 Subject: [PATCH 2/2] Add Glama score badge --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 9e3bf9943..ae80f62c8 100644 --- a/README.md +++ b/README.md @@ -2089,7 +2089,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to - [roomi-fields/notebooklm-mcp](https://github.com/roomi-fields/notebooklm-mcp) [![notebooklm-mcp MCP server](https://glama.ai/mcp/servers/@roomi-fields/notebooklm-mcp/badges/score.svg)](https://glama.ai/mcp/servers/@roomi-fields/notebooklm-mcp) 📇 🏠 🍎 🪟 🐧 - Full automation of Google NotebookLM — Q&A with citations, audio podcasts, video, content generation, source management, and notebook library. MCP + HTTP REST API. - [rushikeshmore/CodeCortex](https://github.com/rushikeshmore/CodeCortex) [![codecortex MCP server](https://glama.ai/mcp/servers/@rushikeshmore/codecortex/badges/score.svg)](https://glama.ai/mcp/servers/@rushikeshmore/codecortex) 📇 🏠 🍎 🪟 🐧 - Persistent codebase knowledge layer for AI coding agents. Pre-digests codebases into structured knowledge (symbols, dependency graphs, co-change patterns, architectural decisions) via tree-sitter native parsing (28 languages) and serves via MCP. 14 tools, ~85% token reduction. Works with Claude Code, Cursor, Codex, and any MCP client. - [s60yucca/mnemos](https://github.com/s60yucca/mnemos) [![s60yucca/mnemos MCP server](https://glama.ai/mcp/servers/s60yucca/mnemos/badges/score.svg)](https://glama.ai/mcp/servers/s60yucca/mnemos) 🏎️ 🏠 🍎 🪟 🐧 - Persistent memory engine for AI coding agents. Stores architecture decisions, bug root causes, and project conventions across sessions. Single Go binary with embedded SQLite, FTS5 search, context assembly within token budgets, and autopilot setup for Claude Code, Kiro, and Cursor. -- [seanmarkwei/agentram-mcp](https://github.com/seanmarkwei/agentram-mcp) 📇 ☁️ - Persistent memory for AI agents through a simple key-value HTTP API. No vector database or embeddings required. Store, retrieve, search, and share memory across agents with shared namespaces and TTL support. `npx -y agentram-mcp` +- [seanmarkwei/agentram-mcp](https://github.com/seanmarkwei/agentram-mcp) 📇 ☁️ [![agentram-mcp MCP server](https://glama.ai/mcp/servers/seanmarkwei/agentram-mcp/badges/score.svg)](https://glama.ai/mcp/servers/seanmarkwei/agentram-mcp) - Persistent memory for AI agents through a simple key-value HTTP API. No vector database or embeddings required. Store, retrieve, search, and share memory across agents with shared namespaces and TTL support. `npx -y agentram-mcp` - [SagaPeak/artifacta-mcp](https://github.com/SagaPeak/artifacta-mcp) [![SagaPeak/artifacta-mcp MCP server](https://glama.ai/mcp/servers/SagaPeak/artifacta-mcp/badges/score.svg)](https://glama.ai/mcp/servers/SagaPeak/artifacta-mcp) 🎖️ 📇 🐍 ☁️ 🍎 🪟 🐧 - The artifact store for AI agents. Every output your agents produce — persisted, retrievable, shareable. Across runs, sessions, and tools. Session/agent metadata, content-hash dedup, expiring share links; 11 tools with path-confined uploads and destructive actions gated by default. TypeScript (`npx @artifacta-mcp/mcp`) and Python (`pipx run artifacta-mcp`). - [SaravananJaichandar/world-model-mcp](https://github.com/SaravananJaichandar/world-model-mcp) [![SaravananJaichandar/world-model-mcp MCP server](https://glama.ai/mcp/servers/SaravananJaichandar/world-model-mcp/badges/score.svg)](https://glama.ai/mcp/servers/SaravananJaichandar/world-model-mcp) 🐍 🏠 🍎 🪟 🐧 - Temporal knowledge graph for codebases. Captures decision traces, links test failures to code changes, learns co-edit patterns, predicts regression risk, and enforces learned constraints at the edit boundary via a PreToolUse hook. 22 MCP tools, 9 SQLite databases with FTS5, supports Python/TypeScript/JavaScript/Solidity/Go/Rust/Java. Install via `pip install world-model-mcp`. - [sachitrafa/YourMemory](https://github.com/sachitrafa/YourMemory) [![sachitrafa/YourMemory MCP server](https://glama.ai/mcp/servers/sachitrafa/YourMemory/badges/score.svg)](https://glama.ai/mcp/servers/sachitrafa/YourMemory) 🐍 🏠 🍎 🪟 🐧 - Persistent memory for AI agents with Ebbinghaus forgetting-curve decay, hybrid BM25+vector retrieval, and entity graph for multi-hop reasoning. Memories auto-prune by importance and recall rate. Built-in browser dashboard, multi-agent support, and `yourmemory ask` for zero-API-call local queries. `pip install yourmemory`