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Hacker News - Newest: "LLM"

GitHub - lechmazur/position_bias: A benchmark for testing whether LLM judges keep the same preference when two lightly edited versions of the same story are shown in opposite orders. Flex routing (EU and EFTA) Dark Factories: Retooling for LLM Velocity Ask HN: What would be the impact of a LLM output injection attack? GitHub - AronDaron/dataset-generator: No-code desktop app for generating high-quality synthetic datasets to fine-tune LLMs — plan-then-execute pipeline, LLM-as-judge, HuggingFace upload. GitHub - Oaklight/llm-rosetta: Production-ready LLM API translation layer for Python — bidirectional conversion between OpenAI, Anthropic & Google formats via hub-and-spoke IR. Optional API gateway. Streaming & non-streaming. Zero core deps. Contributions welcome! GitHub - browser-use/browser-harness: Self-healing browser harness that enables LLMs to complete any task. GitHub - moeen-mahmud/remen: Remen turns thoughts into something you can return to Analyzing 156 LLM Launch Posts on Hacker News ChatGPT vs Gemini vs Claude: The Best LLM Subscription You Should Buy GitHub - salaamalykum/quran-semantic-search: High-density RAG Semantic Search Engine & Quran Corpus (GEO/SEO Architecture) GitHub - NVIDIA/TensorRT-LLM: TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way. The State of LLM Bug Bounties in 2026 Operational Readiness Criteria for Tool-Using LLM Agents Meshcore: Architecture for a Decentralized P2P LLM Inference Network How an LLM becomes more coherent as we train it GitHub - seetrex-ai/laimark GitHub - Jossifresben/BibCrit: AI-assited biblical textual criticism GitHub - wastedcode/memex: File system based wiki, maintained by Claude 99helpers.com GitHub - cliver-project/AITrigram GitHub - unbody-io/adapt: A self-evolving memory layer for AI agents. GitHub - hb20007/awesome-gen-ai-fails: A list of incidents where reliance on generative AI and LLMs resulted in harm to companies, individuals, or society GitHub - nevenkordic/localmind: Run any local LLM with persistent memory and context. CLI agent over Ollama with SQLite-backed hybrid recall. No cloud. Ask HN: What are the machine requirements for a LLM like Llama-3.1-8B? Faster LLM Inference via Sequential Monte Carlo grpo explained: group relative policy optimization for llm finetuning - cgft Stop comparing price per million tokens: the hidden LLM API costs · TensorZero Andrej Karpathy's LLM Wiki Is a Bad Idea GitHub - GG-QandV/mnemostroma: Offline RAM-first cognitive leer/coprocessor for AI agents and robotics. Solves "Context Abandonment" with 20-80ms latency using a dual-thread biomimetic memory architecture (ONNX + SQLite WAL). mempalace/agent at agent · skorotkiewicz/mempalace GitHub - Nyquest-ai/nyquest-rust-fullstack-pub: Nyquest — Semantic Compression Proxy for LLMs. 350+ rules, local LLM stage, 15-75% token savings. Full Rust stack. GitHub - TheoV823/mneme: Enforce architectural decisions in AI-assisted development. GitHub - klemenvod/TokenBrawl: A 1v1 Bomberman-style game where two LLM agents play autonomously against each other. No human plays — you watch the AIs fight. Each agent receives a text description of the board state, reasons about it, and outputs a move as JSON. The game engine executes it. Introducing the Common AI Provider: LLM and AI Agent Support for Apache Airflow Power Circuit AI: Designing Power Electronic Circuits for Motor Drives with Generative Artificial Intelligence Ask HN: How to program with IDE and LLM on CPU locally? Show HN: Agent-cache – Multi-tier LLM/tool/session caching for Valkey and Redis Bonsai 1-bit WebGPU - a Hugging Face Space by webml-community The LLM Fallacy: Misattribution in AI-Assisted Cognitive Workflows Ask HN: Simple tooling for local LLM code critique without IDE integration? Can a General LLM Diagnose a DICOM Slice? A 10-Case Public Benchmark Charts-of-Thought: Enhancing LLM Visualization Literacy (PDF, 2026) GitHub - Mesh-LLM/mesh-llm: Distributed AI/LLM for the people. Share compute privately or publicly to power your agents and chat. GitHub - seamus-brady/springdrift: A persistent runtime for long-lived LLM agents Writing an LLM from scratch, part 32k -- Interventions: training a better model locally with gradient accumulation Ask HN: Which LLM model and agentic CLI are you using for local development? GitHub - wayneColt/modelcascade: Route local. Escalate smart. Never overspend. Open-source multi-model cascade routing for autonomous agents. LLM pricing is 100x harder than you think GitHub - asakin/llm-primer: Pre-warmed Claude Code sessions in tmux. No startup wait. GitHub - EggerMarc/chat-rs: A multi-provider LLM framework for Rust. GitHub - SynapseKit/SynapseKit: Minimal, async-first Python framework for production LLM apps- 2 hard deps, no magic, no SaaS. A Claude Skill that Makes LLM Paragraphs More Bearable Does Gas Town 'steal' usage from users' LLM credits & paid services to improve itself? What's Claude Code Actually Doing? Open the Black Box with the Arthur Engine Milla Jovovich's New Open Source LLM Memory App and the Dark Code Problem Your intuition of LLM token usage might be wrong Show HN: Bloomberg Terminal for LLM ops – free and open source GitHub - 0xchamin/mcptube: Transform YouTube videos into a compounding knowledge base with transcripts, vision analysis, and agentic search. Works as an MCP server for Claude, Copilot & more. Show HN: Open KB: Open LLM Knowledge Base Your LLM is a compiler, not a runtime GitHub - sapountzis/Unslop: A Web Feed That Deserves You crates.io: Rust Package Registry Beyond Karpathy's LLM-Wiki: The Necessity of Cognitive Governance GitHub - amitshekhariitbhu/llm-internals: Learn LLM internals step by step - from tokenization to attention to inference optimization. GitHub - parallem-ai/parallem: An expressive library for running agents with the Batch API. GitHub - stfurkan/pi-llm LLM-Wiki Show HN: Formal – Formal verification for AI-generated code using Lean 4 LRTS – Regression testing for LLM prompts (open source, local-first) LLM Wiki Skill: Build a Second Brain with Claude Code and Obsidian I built an LLM Wiki and RAG solution: here's a demo for a security KB The biggest advance in AI since the LLM Predict-Rlm: The LLM Runtime That Lets Models Write Their Own Control Flow the-synthetic-library/the-synthetic-mind at main · joshferrer1/the-synthetic-library GitHub - yisding/reviewwiggum GitHub - Donnyb369/mcp-spine: Context Minifier & State Guard — Local-first MCP middleware proxy GitHub - Beledarian/wgpu-llm: A from-scratch LLM inference engine that uses wgpu (the cross-platform WebGPU implementation) to dispatch WGSL compute shaders for every math operation a Transformer needs. No CUDA. No Python. No massive framework dependencies. Just Rust, raw shaders, and your GPU. GitHub - anitiue/Hindsight: An experience-driven self-improvement framework for LLM agents — 基于经验的 LLM Agent 自我改进框架 GitHub - stef41/lmscan: 🔍 Detect AI-generated text and fingerprint which LLM wrote it. Open-source GPTZero alternative. Zero dependencies, works offline. GitHub - alainnothere/AmdPerformanceTesting: Amd Performance Testing Ask HN: Is a purely Markdown-based CRM a terrible idea? Optimized for LLM agents Context Engineering - LLM Memory and Retrieval for AI Agents | Weaviate little_helper_tui/letter.md at main · sleepyeldrazi/little_helper_tui GitHub - EvanZhouDev/umr: The Unified Model Registry for all your local AI apps. GitHub - JordanCT/VigIA-Orchestrator Your Agent Is Mine: Measuring Malicious Intermediary Attacks on the LLM Supply Chain A Taxonomy of RL Environments for LLM Agents Llama LLM Network Feture GitHub - genedeng-ca/ai-mac-migration: AI-powered Mac-to-Mac migration tool - replace Apple Migration Assistant with intelligent, selective transfer using local LLMs GitHub - lunargate-ai/gateway: High-performance self-hosted AI gateway (OpenAI-compatible) with routing, retries, and streaming GitHub - AuthBits/webmcp: A lightweight, prompt-driven MCP web research server for high-quality LLM powered information extraction. Externalization in LLM Agents: A Unified Review of Memory, Skills, Protocols and Harness Engineering Springdrift: An Auditable Persistent Runtime for LLM Agents with Case-Based Memory, Normative Safety, and Ambient Self-Perception High-Stakes Personalization: Rethinking LLM Customization for Individual Investor Decision-Making From Static Templates to Dynamic Runtime Graphs: A Survey of Workflow Optimization for LLM Agents HUOZIIME: An On-Device LLM-enhanced Input Method for Deep Personalization TIDE: Token-Informed Depth Execution for Per-Token Early Exit in LLM Inference Characterizing WebGPU Dispatch Overhead for LLM Inference Across Four GPU Vendors, Three Backends, and Three Browsers LLM Targeted Underperformance Disproportionately Impacts Vulnerable Users
GitHub - xyTom/coding-tools-mcp: Give any AI agent the ability to code
xytom · 2026-06-19 · via Hacker News - Newest: "LLM"

Coding Tools MCP is a model-neutral coding-agent runtime MCP server. It exposes local coding primitives to any MCP client:

inspect repo -> search/read files -> apply structured patches -> run tests/commands
-> interact with stdin sessions -> inspect git status/diff

It is not a prompt wrapper. It does not expose external agent accounts, memory, cloud tasks, web search, image generation, model routing, plugin marketplace, or subagent orchestration as MCP tools.

Documentation Map

Quickstart

Install the published command from PyPI:

curl -fsSL https://raw.githubusercontent.com/xyTom/coding-tools-mcp/main/scripts/install.sh | bash

Install and start local Streamable HTTP against a workspace:

curl -fsSL https://raw.githubusercontent.com/xyTom/coding-tools-mcp/main/scripts/install.sh \
  | bash -s -- --start --workspace /path/to/repo

Install and expose a read-only bearer-token tunnel:

curl -fsSL https://raw.githubusercontent.com/xyTom/coding-tools-mcp/main/scripts/install.sh \
  | bash -s -- --tunnel cloudflared --auto-install-tunnel --workspace /path/to/repo

Or, from this checkout:

Run the published package without a persistent install:

uvx coding-tools-mcp --workspace .

Use stdio for MCP clients:

uvx coding-tools-mcp --stdio --workspace /path/to/repo

If you are working from this checkout instead of a published package:

Pass a different workspace, host, port, or extra server flags with Make variables:

make start MCP_WORKSPACE=/path/to/repo MCP_PORT=8000 MCP_ARGS="--permission-mode trusted"

If dependencies are missing, install the runtime in editable mode:

python -m pip install -e ".[dev]"

HTTP endpoint:

http://127.0.0.1:8765/mcp

Install the optional image extra when you want view_image auto-resize support:

python -m pip install -e ".[image]"

Stdio:

coding-tools-mcp --stdio --workspace /path/to/repo

Set CODING_TOOLS_MCP_TRACE=1 to emit redacted JSON tool-call trace events to stderr for local debugging. Logs stay off stdout so stdio JSON-RPC remains clean.

By default, exec_command passes a core shell environment only. For local toolchains that depend on inherited environment variables, such as MSVC developer prompts, start with:

CODING_TOOLS_MCP_SHELL_ENV_INHERIT=all coding-tools-mcp --workspace /path/to/repo

inherit=all still filters secret-looking and loader/startup variables unless dangerous mode is also enabled. For local development with dependency downloads, shell expansion, and inline interpreter snippets, use:

coding-tools-mcp --permission-mode trusted --workspace /path/to/repo

--allow-network remains available as a compatibility flag when you only want to open network-looking commands. If your MCP client does not support permission elicitation and you explicitly want to disable exec_command permission gates inside an isolated container or VM, start with:

coding-tools-mcp --permission-mode dangerous --workspace /path/to/repo

This disables exec_command permission gates such as network-looking commands, destructive command checks, shell expansion, inline scripts, and sensitive env checks. Workspace path boundaries for direct file tools still apply. --dangerously-skip-all-permissions remains as a compatibility alias.

MCP Client Examples

Generic stdio client:

[mcp_servers.coding_tools]
command = "uvx"
args = ["coding-tools-mcp", "--stdio", "--workspace", "/path/to/repo"]

Claude Code:

{
  "mcpServers": {
    "coding-tools": {
      "command": "uvx",
      "args": ["coding-tools-mcp", "--stdio", "--workspace", "/path/to/repo"]
    }
  }
}

Cursor:

{
  "mcpServers": {
    "coding-tools": {
      "command": "uvx",
      "args": ["coding-tools-mcp", "--stdio", "--workspace", "/path/to/repo"]
    }
  }
}

Generic Streamable HTTP clients should use MCP protocol version 2025-06-18 and point at http://127.0.0.1:8765/mcp.

Remote MCP

For remote MCP clients and local development over an HTTPS tunnel, keep the server bound to loopback and expose the tunnel URL with the safest profile your client can use. Anonymous tunnel testing should use read-only mode:

CODING_TOOLS_MCP_AUTH_MODE=noauth \
CODING_TOOLS_MCP_TOOL_PROFILE=read-only \
./scripts/tunnel.sh cloudflared /path/to/repo

Configure the remote MCP client with the HTTPS tunnel URL:

URL: https://<tunnel-host>/mcp

The tunnel scripts support cloudflared, ngrok, and Microsoft Dev Tunnel. If the selected tunnel CLI is missing, the script asks before installing it:

scripts/tunnel.sh cloudflared /path/to/repo
scripts/tunnel.sh ngrok /path/to/repo
scripts/tunnel.sh devtunnel /path/to/repo

For clients that support custom headers, use bearer-token auth with Authorization: Bearer <token>. For MCP clients that speak OAuth 2.1 Authorization Code + PKCE, use CODING_TOOLS_MCP_AUTH_MODE=oauth with scripts/tunnel.sh (or scripts/install.sh --auth-mode oauth). The server can infer its OAuth issuer from the tunnel request URL, so one-shot tunnels like cloudflared work without setting CODING_TOOLS_MCP_SERVER_URL before startup; set it only when you want to pin a stable issuer. The script prints a generated OAuth password, accepts any non-empty client_id by default, and lets you opt into CODING_TOOLS_MCP_OAUTH_CLIENT_ID/CODING_TOOLS_MCP_OAUTH_CLIENT_SECRET only when you need to lock down a confidential client. Clients that cannot send custom bearer headers and do not speak OAuth should use anonymous read-only mode only for local/testing tunnels, or be placed behind an external auth proxy for production use.

See docs/remote-mcp.md for the exact modes and security notes.

Tool Profiles

  • full: exposes all tools with truthful annotations. This is the default for backward compatibility.
  • read-only: recommended for remote or safe-mode clients; exposes only inspection tools, git read tools, image viewing, and default-cwd helpers.
  • compat-readonly-all: exposes all tools but advertises every tool as read-only for clients that gate availability on readOnlyHint. This is not a safety mode; mutation-capable tools such as apply_patch, exec_command, write_stdin, and kill_session can still mutate local state.

Tools

P0 tools exposed by default:

  • server_info
  • get_default_cwd
  • set_default_cwd
  • read_file
  • list_dir
  • list_files
  • search_text
  • apply_patch
  • exec_command
  • write_stdin
  • kill_session
  • git_status
  • git_diff
  • git_log
  • git_show
  • git_blame
  • request_permissions

Additional image tool exposed by default:

  • view_image

For input/output schemas and result envelopes, see docs/tools-and-schemas.md and docs/profile-v0.1.md.

Safety Boundary

The runtime binds one workspace root per server process. Paths are workspace-relative by default. Absolute paths, .. traversal, and symlink escapes are rejected. Recursive listing/search excludes .git, .reference, node_modules, target, dist, build outputs, virtualenvs, and common caches by default.

exec_command runs under policy controls with workspace-bound cwd, configurable shell environment inheritance, timeout, output caps, sensitive-value and loader/startup environment rejection, destructive command checks, network-looking command checks, shell-expansion permission gates, indirect absolute-path checks, cancellation/kill cleanup, session deadline watchdogs, and bounded session buffers. On Linux hosts with Landlock support it also applies filesystem confinement; on Windows, macOS, or Linux hosts without Landlock, command results include a warning and external sandboxing is required before running untrusted commands. This is still not a complete OS/container sandbox; see SECURITY.md.

--permission-mode safe is the default. --permission-mode trusted opens local-development gates while keeping secret filtering and destructive-command checks. --permission-mode dangerous disables exec_command permission gates for operators who accept that risk inside an isolated runner. Do not use dangerous mode for untrusted workspaces or untrusted MCP clients.

Compliance

Compliance and CI commands are documented in docs/ci-and-tests.md. The checked-in report files are generated artifacts; inspect their suite field before treating them as full compliance evidence.

Dogfood And Benchmark

Dogfood and SWE-bench notes live in docs/dogfood.md, docs/swe-bench.md, and BENCHMARK.md. This repository does not claim a model-generated SWE-bench leaderboard result.

Development Commands

make lint
make typecheck
make test
make compliance
make ci

See docs/ci-and-tests.md for the full test matrix.

License

This project is source-available, not open source. See LICENSE. Internal evaluation, development, testing, and security review are permitted; redistribution, hosted third-party service use, and production commercial use require prior written permission.