Synaptic
★ 31
vs
CALM
★ 17
Synaptic vs CALM
Synaptic: Synaptic transforms codebases into a persistent, queryable knowledge graph to enhance understanding and facilitate advanced development tasks. It uses this graph to answer structural and architectural queries, trace impact, plan refactors, and integrate with AI coding assistants.; CALM: CALM (Coding Agent Liveness Map) provides AI coding agents with a live, graph-verified map of the codebase, enabling them to understand dependencies and structural relationships before making changes. This ensures safer and more accurate code edits, preventing common pitfalls like breaking call sites or critical components due to lack of visibility.
01
TL;DR
SynapticCode Assistant · ★ 31
Understanding Large Codebases: Quickly gain structural clarity, identify "god nodes" or import cycles, and understand surprising cross-module connections in large monorepos or federated repositories.
CALMCode Assistant · ★ 17
Empowering AI agents to safely refactor and edit code directly, by providing a deep understanding of code dependencies and impact.
02
Side-by-Side Comparison
Field
SynapticCALMCategory
Code Assistant
Code Assistant
Stars
★ 31
★ 17
License
AGPL-3.0
MIT
Install Command
cargo install --path bin/synaptic
curl -fsSL https://raw.githubusercontent.com/Eilodon/CALM/main/scripts/install.sh | sh && calm setup --project-root .
Updated
5d ago
2d ago
Open Source
Yes
Yes
Tags
code analysis, knowledge graph, static analysis
Code Intelligence, AI Agent, Call Graph
03
Features
Synaptic01Multi-language Code Graph Generation: Extracts symbols and relationships across 30+ programming languages using tree-sitter to build a comprehensive code knowledge graph.
02Advanced Code Querying & Analysis: Supports structural and architectural queries (SYNQL), reverse impact analysis ("what depends on this?"), and time-travel diffing across Git history.
03Safe Refactoring & Change Forecasting: Generates confidence-scored execution plans for refactors (rename, move, extract) and forecasts the blast radius, at-risk tests, and potential cycles of a change before it's made.
04AI Assistant Integration via MCP Server: Exposes 28 read-only tools over an MCP server (stdio or HTTP) for AI coding assistants to leverage the graph for tasks like subgraph search, impact prediction, and structural analysis.
CALM01Real-time, Graph-Verified Codebase Map: Provides full call graphs for 13 languages out of the box (24 languages parsed in total), showing actual dependencies rather than similarity guesses.
02Hard Safety Gates on Write Path: Enforces hash-verified and syntax-checked edits, with hub/high-risk symbols requiring explicit confirmation and review of callers before changes are committed.
03Confidence-Graded Call Edges with Compiler Verification: Call edges are confidence-graded (textual → inferred → resolved → formal), with SCIP/LSP overlays upgrading best-guess edges to compiler-verified ground truth for 12 languages.
04Automated Codebase Health Reporting: Generates fitness reports based on metrics like hub concentration, dead code rate, complexity, and architectural boundary violations, queryable mid-session or enforceable in CI.
05Local-First and Privacy-Preserving Operation: Runs entirely on your machine with no code leaving for indexing or editing, using an MIT license and vendored embedding models for offline use.
04
Use Cases
Synaptic↳Understanding Large Codebases: Quickly gain structural clarity, identify "god nodes" or import cycles, and understand surprising cross-module connections in large monorepos or federated repositories.
↳Pre-commit Impact Assessment: Before making a change, forecast its blast radius, identify at-risk tests, and detect potential new cycles to prevent regressions.
↳Automated Code Auditing: Audit SQL code for performance and security issues (e.g., SQL injection, missing indexes, RLS gaps) directly from the graph.
↳AI-powered Developer Workflow: Integrate with AI coding assistants to enable smarter, graph-aware responses for tasks like context retrieval, refactoring plans, and architectural queries, reducing token costs significantly.
CALM↳Empowering AI agents to safely refactor and edit code directly, by providing a deep understanding of code dependencies and impact.
↳Ensuring code quality and architecture compliance in CI/CD pipelines, by automatically flagging dead code, high-complexity functions, and boundary violations.
↳Onboarding developers to new codebases or areas by offering an interactive, live map of the project's structure and hotspots.
↳Facilitating secure and validated code modifications within various IDEs and AI client environments, preventing unintended breakages.
FAQ
FAQ
What is the difference between Synaptic and CALM?
Both Synaptic and CALM are in the Code Assistant category. Synaptic has 31 stars, while CALM has 17 stars.
Which is better, Synaptic or CALM?
The best choice depends on your use case. Choose Synaptic if Understanding Large Codebases: Quickly gain structural clarity, identify "god nodes" or import cycles, and understand surprising cross-module connections in large monorepos or federated repositories., and CALM if Empowering AI agents to safely refactor and edit code directly, by providing a deep understanding of code dependencies and impact..
Is Synaptic free or open source?
Yes, Synaptic is open source on GitHub (AGPL-3.0).
Is CALM free or open source?
Yes, CALM is open source on GitHub (MIT).
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