Python interface for the SCIP Optimization Suite
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Updated
Sep 16, 2026 - Cython
Python interface for the SCIP Optimization Suite
SCIP - Solving Constraint Integer Programs
Symbol Delta Ledger (SDL-MCP) is a policy-centered context budget layer for coding agents: Symbol-graph intelligence combined with precision tools. It turns sprawling codebases into compact, high-signal context that saves tokens, speeds up workflows, and improves agent output.
Extensible Combinatorial Optimization Learning Environments
Deterministic, local-first memory and guardrails for AI coding agents with no LLM in the hot path.
We handle what engineers and IDEs won't: generating and maintaining technical documentation for your codebase, while also providing search with dependency-aware context to help your AI tools understand your codebase and its conventions.
Optimally allocate poker chips using constrained, nonlinear optimization
Code intelligence for AI assistants - MCP server, CLI, and HTTP API with symbol navigation, impact analysis, and architecture mapping
CLI built for AI agents to help navigate codebases better. An alternative to grep/find/glob
Multi-repo semantic code search MCP server in Rust — hybrid vector + BM25 retrieval, tree-sitter AST chunking, fully offline. For OpenCode, Claude Code, Cursor, and any MCP client.
DataSAIL is a tool to split datasets while reducing information leakage.
Python interface and modeling environment for GCG
SCIP indexer for Kotlin. Implemented as a SemanticDB compiler plugin.
Local repo-intelligence index + MCP server: semantic search, symbol/graph navigation, impact-surface preflight, git + GitHub papertrail, and a source-anchored memory graph.
Generators for Combinatorial Optimization
Template for deploying an optimization model accessible via a web service based on FastAPI, mongodb and celery
To associate your repository with the scip topic, visit your repo's landing page and select "manage topics."