[{"_1":2,"_254":-5,"_255":-5},"loaderData",{"_3":4,"_28":29,"_30":31,"_32":33,"_215":216},"root",{"_5":6,"_16":17},"toasts",[7,14],{"_8":9,"_10":11,"_12":13},"uid","32b2e10a-18ae-4881-b11c-3f6819f1e3b2","title","This MCP server does not support inspection","type","error",{"_8":15,"_10":11,"_12":13},"81a12f1c-053e-4656-851f-42134ae8d27b","visitor",{"_18":19,"_20":21},"viewportWidth",1280,"visitorSession",{"_22":23,"_25":-5,"_8":26,"_27":-5},"attributes",[24],"BOT","membership","BQexe2iOmM","userAccount","routes/_public/_layout",{},"routes/_public/mcp/servers/~namespace/_layout",{},"routes/_public/mcp/servers/~namespace/~slug/_pages/_layout",{"_34":-5,"_35":36,"_37":38,"_135":136},"githubUser","maintainer",false,"mcpServer",{"_39":40,"_41":42,"_22":53,"_60":61,"_62":61,"_63":64,"_69":70,"_90":-5,"_91":92,"_93":36,"_94":95,"_79":106,"_107":84,"_108":-5,"_109":-5,"_110":-5,"_111":112,"_119":-5,"_120":121,"_126":-5,"_102":80,"_127":128,"_131":-5,"_8":132,"_133":134},"addedAt",["D",1742552442014],"argumentsJsonSchema",{"_43":44,"_50":51,"_12":52},"properties",{"_45":46},"GEMINI_API_KEY",{"_47":48,"_12":49},"description","Your Gemini API key for LearnLM functionality","string","required",[45],"object",[54,55,56,57,58,59,54],"author:claimed","category:knowledge-and-memory","category:developer-tools","hosting:remote-capable","language:typescript","license_grade:f","descriptionMarkdown","A metacognitive advisor for Claude that provides strategic guidance, plan distillation, and mistake tracking to enhance Claude's reasoning capabilities.","descriptionPlainText","githubProject",{"_65":66,"_67":68},"readme","# Wisdom Layer MCP\n\nA metacognitive advisor for Claude powered by LearnLM.\n\n## Overview\n\nThe Wisdom Layer MCP is a specialized Model Context Protocol server designed to enhance Claude's reasoning capabilities. It creates a \"wisdom layer\" that acts as a strategic questioner, advisor, and complexity reducer for Claude, helping it to avoid recurring mistakes and achieve better results.\n\n## Features\n\n- **Strategic Metacognitive Advisor**: Analyzes Claude's thinking process and provides targeted advice\n- **Plan Distillation**: Forces ultra-simplified summaries for clarity and focus\n- **Mistake Tracking**: Learns from past mistakes to avoid future ones\n- **LearnLM Integration**: Powered by Google's LearnLM/Gemini API for metacognitive guidance\n\n## Tools\n\n### 1. wisdom_advise\n\nA constraint-free strategic advisor that works like a challenging mentor:\n\n- Takes raw, unfiltered context to avoid Claude's cognitive biases\n- Provides user alignment checks and complexity reduction\n- Offers pattern-breaking questions and perspectives\n- Suggests appropriate MCP tools to use\n- Learns from past mistake patterns\n\n```\n\nwisdom\nwisdom_advise\n\n{\n \"plan\": \"My current plan is...\",\n \"userRequest\": \"Original request from user\",\n \"thinkingLog\": \"Raw sequential thinking output\",\n \"availableTools\": [\"tool1\", \"tool2\"]\n}\n\n\n```\n\n### 2. wisdom_canvas\n\nA distillation tool for final plans:\n\n- Forces ultra-simplified plan representation\n- Includes \"why\" section to justify approach\n- Creates a checkpoint before implementation\n- Serves as a reference during execution\n\n```\n\nwisdom\nwisdom_canvas\n\n{\n \"plan\": \"Detailed plan to distill\",\n \"userRequest\": \"Original request from user\"\n}\n\n\n```\n\n### 3. wisdom_log\n\nA mistake tracking system:\n\n- One-sentence descriptions of mistakes made and corrected\n- Categorizes and tallies recurring mistakes\n- Creates a persistent learning feedback loop\n- Read by LearnLM to provide targeted guidance\n\n```\n\nwisdom\nwisdom_log\n\n{\n \"mistake\": \"One-sentence description of the mistake\",\n \"category\": \"mistake-category\",\n \"solution\": \"How it was corrected\"\n}\n\n\n```\n\n## Installation\n\n### Prerequisites\n\n- Node.js (v18.0.0 or higher)\n- npm (v7.0.0 or higher)\n- A Gemini API key for LearnLM functionality\n\n### Installation Steps\n\n```bash\n# Install globally\nnpm install -g wisdom-layer-mcp\n\n# Or run directly\nnpx wisdom-layer-mcp\n```\n\n### MCP Configuration\n\nAdd the server to your MCP settings file. For Claude/Cline, this is typically located at:\n- For Claude Desktop: `~/Library/Application Support/Claude/claude_desktop_config.json` (macOS)\n- For VSCode Cline: `~/.config/Code/User/globalStorage/saoudrizwan.claude-dev/settings/cline_mcp_settings.json` (Linux)\n\nAdd the following configuration:\n\n```json\n{\n \"mcpServers\": {\n \"wisdom\": {\n \"command\": \"wisdom-layer-mcp\",\n \"args\": [],\n \"env\": {\n \"GEMINI_API_KEY\": \"your-gemini-api-key\"\n },\n \"disabled\": false,\n \"autoApprove\": []\n }\n }\n}\n```\n\n## Usage Pattern\n\nThe ideal usage pattern for Claude:\n\n1. Claude uses sequential thinking to formulate an initial plan\n2. Claude calls wisdom_advise with raw context\n3. Claude refines its approach based on LearnLM's advice\n4. Claude finalizes with wisdom_canvas for ultra-clarity\n5. Claude implements the solution\n6. Claude logs any lessons learned in wisdom_log\n\nThis creates a metacognitive layer that helps Claude think better about its own thinking.\n\n## Development\n\n```bash\n# Clone the repository\ngit clone https://github.com/yourusername/wisdom-layer-mcp.git\ncd wisdom-layer-mcp\n\n# Install dependencies\nnpm install\n\n# Build\nnpm run build\n\n# Start development mode\nnpm run dev\n```\n\n## License\n\nMIT","url","https://github.com/pv-bhat/wisdom-layer-mcp","githubRepository",{"_71":72,"_73":74,"_75":76,"_77":78,"_79":80,"_81":82,"_86":87,"_88":-5,"_89":87},"defaultBranch","main","fullName","PV-Bhat/wisdom-layer-mcp","githubTreeId",96802,"language","TypeScript","name","wisdom-layer-mcp","owner",{"_83":84,"_8":85},"login","PV-Bhat","OWWhGQA1tF","recentStargazers",1,"spdxLicense","stargazers","glamaJson","id",2102,"inspectable","integrations",[96],{"_97":98,"_47":104,"_8":105},"brand",{"_99":100,"_79":101,"_102":103},"logoSvgPath","M12.48 10.92v3.28h7.84c-.24 1.84-.853 3.187-1.787 4.133-1.147 1.147-2.933 2.4-6.053 2.4-4.827 0-8.6-3.893-8.6-8.72s3.773-8.72 8.6-8.72c2.6 0 4.507 1.027 5.907 2.347l2.307-2.307C18.747 1.44 16.133 0 12.48 0 5.867 0 .307 5.387.307 12s5.56 12 12.173 12c3.573 0 6.267-1.173 8.373-3.36 2.16-2.16 2.84-5.213 2.84-7.667 0-.76-.053-1.467-.173-2.053H12.48z","Google","slug","google","Leverages Google's LearnLM/Gemini API to provide metacognitive guidance for Claude, analyzing thinking processes and offering targeted advice to improve reasoning outcomes.","g08y7cqy2p","Wisdom Layer MCP","namespace","npmPackage","prompts","redditPostForeignId","relatedMcpServerIds",[113,114,115,116,117,118],1471,1519,596,716,1423,1655,"resources","scores",{"_122":123,"_124":-5,"_125":-5},"license",0,"quality","security","simpleIcon","supportedPlatforms",[129,130],"MACOS","LINUX","tools","89v7jbn2c8","updatedAt",["D",1742557335346],"meta",[137,139,141,148,151,153,156,159,162,165,168,170,173,176,178,180,182,184,186],{"_10":138},"Wisdom Layer MCP | Glama",{"_140":61,"_79":47},"content",{"_142":143,"_144":145,"_146":147},"href","https://glama.ai/mcp/servers/@PV-Bhat/wisdom-layer-mcp","rel","canonical","tagName","link",{"_140":106,"_149":150},"property","og:title",{"_140":61,"_149":152},"og:description",{"_140":154,"_149":155},"https://glama.ai/logo.png","og:logo",{"_140":157,"_149":158},"https://glama.ai/mcp/servers/@PV-Bhat/wisdom-layer-mcp/og-image","og:image",{"_140":160,"_149":161},"630","og:image:height",{"_140":163,"_149":164},"1200","og:image:width",{"_140":166,"_149":167},"website","og:type",{"_140":143,"_149":169},"og:url",{"_140":171,"_149":172},"ChatGPT alternative for power users","og:site_name",{"_140":174,"_79":175},"summary_large_image","twitter:card",{"_140":171,"_79":177},"twitter:title",{"_140":61,"_79":179},"twitter:description",{"_140":157,"_79":181},"twitter:image",{"_140":160,"_79":183},"twitter:image:height",{"_140":163,"_79":185},"twitter:image:width",{"_187":188},"script:ld+json",{"_189":190,"_191":192},"@context","http://schema.org","@graph",[193],{"_189":194,"_195":196,"_197":198},"https://schema.org","@type","BreadcrumbList","itemListElement",[199,205,209,213],{"_195":200,"_201":202,"_79":203,"_204":87},"ListItem","item","https://glama.ai/","Glama","position",{"_195":200,"_201":206,"_79":207,"_204":208},"https://glama.ai/mcp","MCP",2,{"_195":200,"_201":210,"_79":211,"_204":212},"https://glama.ai/mcp/servers","Servers",3,{"_195":200,"_201":143,"_79":106,"_204":214},4,"routes/_public/mcp/servers/~namespace/~slug/_pages/_explorer/blob/~branch/~/_route",{"_217":218,"_222":72,"_37":223,"_240":241,"_242":243},"blob",{"_140":219,"_220":221},"node_modules/\nbuild/\n.env\n.DS_Store\n*.log","fileName",".gitignore","branch",{"_39":224,"_41":225,"_22":229,"_60":61,"_62":61,"_63":230,"_69":231,"_90":-5,"_91":92,"_93":36,"_94":233,"_79":106,"_107":84,"_108":-5,"_109":-5,"_110":-5,"_111":236,"_119":-5,"_120":237,"_126":-5,"_102":80,"_127":238,"_131":-5,"_8":132,"_133":239},["D",1742552442014],{"_43":226,"_50":228,"_12":52},{"_45":227},{"_47":48,"_12":49},[45],[54,55,56,57,58,59,54],{"_65":66,"_67":68},{"_71":72,"_73":74,"_75":76,"_77":78,"_79":80,"_81":232,"_86":87,"_88":-5,"_89":87},{"_83":84,"_8":85},[234],{"_97":235,"_47":104,"_8":105},{"_99":100,"_79":101,"_102":103},[113,114,115,116,117,118],{"_122":123,"_124":-5,"_125":-5},[129,130],["D",1742557335346],"path","","treeMembers",[244,247,248,250,252],{"_240":245,"_12":246},"src","tree",{"_240":221,"_12":217},{"_240":249,"_12":217},"package.json",{"_240":251,"_12":217},"README.md",{"_240":253,"_12":217},"tsconfig.json","actionData","errors"]