neuron-explorer
Steering-first neuron explorer for Qwen3.5-4B: push every MLP neuron, keep every rollout, browse the results
The most comprehensive code intelligence MCP server for AI coding agents. 40+ tools, 30+ languages, 9 agent integrations. Pre-indexed semantic knowledge graphs for instant code understanding — fewer t
Developer toolsRust · PythonGitHub @aovestdipaperinoSelf-installOwner unconfirmed
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The most comprehensive code intelligence MCP server for AI coding agents. 40+ tools, 30+ languages, 9 agent integrations. Pre-indexed semantic knowledge graphs for instant code understanding — fewer tokens, fewer tool calls, 100% local.
Taken from the repository README
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Semantic Code Intelligence for AI Coding Agents
AI coding agents waste tokens exploring codebases. Every grep, glob, and file read costs money. On complex tasks, agents spawn multiple Explore sub-agents that scan hundreds of files just to build context.
tokensave gives agents a pre-indexed semantic knowledge graph. Instead of scanning files, the agent queries the graph and gets instant, structured answers -- the right symbols, their relationships, and source code, in one call.
Without tokensave: Agents use grep, glob, and Read to scan files -- many API calls, high token usage.Read the full README ↗The full README is unavailable right now. Read it at the original link. The saved excerpt is shown below.
Semantic Code Intelligence for AI Coding Agents
AI coding agents waste tokens exploring codebases. Every grep, glob, and file read costs money. On complex tasks, agents spawn multiple Explore sub-agents that scan hundreds of files just to build context.
tokensave gives agents a pre-indexed semantic knowledge graph. Instead of scanning files, the agent queries the graph and gets instant, structured answers -- the right symbols, their relationships, and source code, in one call.
Without tokensave: Agents use grep, glob, and Read to scan files -- many API calls, high token usage.Read the full README ↗