Awesome/awesome-mcp-servers
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Requested by the listing bot. The server is already indexed on Glama, which
crawled the public repo on its own; this adds the badge the entry format
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Daniel Francis-Lyon
2026-09-08 06:11:03 -07:00
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@@ -2797,7 +2797,7 @@ Persistent memory storage using knowledge graph structures. Enables AI models to
- [yuelinghuashu/story-cli](https://github.com/yuelinghuashu/story-cli) [![yuelinghuashu/story-cli MCP server](https://glama.ai/mcp/servers/yuelinghuashu/story-cli/badges/score.svg)](https://glama.ai/mcp/servers/yuelinghuashu/story-cli) 📇 🏠 🍎 🪟 🐧 - Git-native Markdown content management CLI with built-in MCP Server. Search, read, write, and govern story/paper/note repositories; auto-generate READMEs, validate configs, export EPUB, and prepare SFT/embedding training data. 9 tools, token-efficient. `npm i -g @yuelinghuashu/story-cli` - [yuelinghuashu/story-cli](https://github.com/yuelinghuashu/story-cli) [![yuelinghuashu/story-cli MCP server](https://glama.ai/mcp/servers/yuelinghuashu/story-cli/badges/score.svg)](https://glama.ai/mcp/servers/yuelinghuashu/story-cli) 📇 🏠 🍎 🪟 🐧 - Git-native Markdown content management CLI with built-in MCP Server. Search, read, write, and govern story/paper/note repositories; auto-generate READMEs, validate configs, export EPUB, and prepare SFT/embedding training data. 9 tools, token-efficient. `npm i -g @yuelinghuashu/story-cli`
- [ni-c/wikijs-mcp](https://github.com/ni-c/wikijs-mcp) [![ni-c/wikijs-mcp MCP server](https://glama.ai/mcp/servers/ni-c/wikijs-mcp/badges/score.svg)](https://glama.ai/mcp/servers/ni-c/wikijs-mcp) 📇 🏠 🍎 🪟 🐧 - Search, read and edit a self-hosted [Wiki.js](https://js.wiki) 2.x, plus its assets, comments, users and groups (62 tools). Wiki.js' default search engine indexes only titles and descriptions, so `search_pages` names the active engine and `grep_pages` searches what is actually written in the pages. `update_page` compares against the moment you read a page and refuses to overwrite an edit saved in between; surgical find-and-replace must match exactly once. Read-only mode, a write path scope, and confirmation tokens on everything destructive. `npx -y @ni-c/wikijs-mcp` - [ni-c/wikijs-mcp](https://github.com/ni-c/wikijs-mcp) [![ni-c/wikijs-mcp MCP server](https://glama.ai/mcp/servers/ni-c/wikijs-mcp/badges/score.svg)](https://glama.ai/mcp/servers/ni-c/wikijs-mcp) 📇 🏠 🍎 🪟 🐧 - Search, read and edit a self-hosted [Wiki.js](https://js.wiki) 2.x, plus its assets, comments, users and groups (62 tools). Wiki.js' default search engine indexes only titles and descriptions, so `search_pages` names the active engine and `grep_pages` searches what is actually written in the pages. `update_page` compares against the moment you read a page and refuses to overwrite an edit saved in between; surgical find-and-replace must match exactly once. Read-only mode, a write path scope, and confirmation tokens on everything destructive. `npx -y @ni-c/wikijs-mcp`
- [dfrancislyondflabc-tech/agentic-recall](https://github.com/dfrancislyondflabc-tech/agentic-recall) 📇 🏠 🍎 🪟 🐧 - Long-term memory across sessions over a folder of plain markdown files. Hybrid retrieval (BM25F + dense vectors + phrase proximity) with an explicit absence verdict: when the corpus does not hold the answer it returns no results and names the query terms that appear nowhere, instead of ranking a least-bad match as though it were one. Embedding model runs locally, nothing leaves the machine. MIT. - [dfrancislyondflabc-tech/agentic-recall](https://github.com/dfrancislyondflabc-tech/agentic-recall) [![dfrancislyondflabc-tech/agentic-recall MCP server](https://glama.ai/mcp/servers/dfrancislyondflabc-tech/agentic-recall/badges/score.svg)](https://glama.ai/mcp/servers/dfrancislyondflabc-tech/agentic-recall) 📇 🏠 🍎 🪟 🐧 - Long-term memory across sessions over a folder of plain markdown files. Hybrid retrieval (BM25F + dense vectors + phrase proximity) with an explicit absence verdict: when the corpus does not hold the answer it returns no results and names the query terms that appear nowhere, instead of ranking a least-bad match as though it were one. Embedding model runs locally, nothing leaves the machine. MIT.
### ⚖️ <a name="legal"></a>Legal ### ⚖️ <a name="legal"></a>Legal
Access to legal information, legislation, and legal databases. Enables AI models to search and analyze legal documents and regulatory information. Access to legal information, legislation, and legal databases. Enables AI models to search and analyze legal documents and regulatory information.