The Tool Every AI Coder
Will Thank You For

One SQLite file. 26 languages & frameworks. 74 MCP tools with LSP code intelligence. Enable semantic search, relationship mapping, and persistent memory for any AI coding agent—completely local and private.

74 MCP Tools31 Core + 38 LSP + 5 Arch
LSP Intelligence4-Tier Auto Detection
Context GraphAI Memory System
Semantic SearchVector Embeddings
Single SQLite File
26 Languages & Frameworks
100% Local & Private
Fast, Parallel Parsing
$curl -LO https://downloads.devscriptor.com/installers/devscriptor-1.2.0-x86_64-unknown-linux-gnu.tar.gz

Or grab the installer for macOS, Linux & Windows

What Devscriptor Does
for AI-Assisted Development

A toolkit built in Rust for turning your codebase into an AI-navigable knowledge graph

Learn more

Built in Rust

High-performance, multi-threaded parsing with memory safety and zero-cost abstractions.

Single SQLite Database

All codebase knowledge in one portable file with SQL querying and vector search.

Code Graph Analysis

Entity extraction, relationship mapping, and architectural pattern recognition.

LSP Code Intelligence

38 LSP tools providing IDE features via 4-tier auto-detection system.

26 Languages & Frameworks

Tree-sitter parsing for web, systems, JVM, .NET, mobile, and the Vue & Svelte frameworks.

Gitignore-Aware Discovery

Parallel file walking with native .gitignore support via ripgrep's ignore engine.

Incremental & Real-time

mtime+size fast-path re-scans, plus a watcher that keeps the graph current as you code.

Context Graph Memory

AI agents that remember across sessions with 9 structured note types.

How It Works

From install to a queryable knowledge graph in five steps

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1

Install

Download the single universal binary for macOS, Linux, or Windows and add it to your PATH.

2

Scan

Point Devscriptor at your codebase. It parses 26 languages & frameworks with gitignore-aware discovery.

3

Analyze

All knowledge stored in SQLite—entities, relationships, and vector embeddings for semantic search.

4

Connect LSP

4-tier auto-detection finds or installs language servers: Config → Bundled → System → VS Code → Auto-install.

5

Query

AI connects via MCP with 74 tools: 31 Core + 38 LSP + 5 Architecture tools.

terminal
# Quick start
$ devscriptor scan ./my-project
$ devscriptor lsp setup
$ devscriptor mcp
Installation

Install in Three Steps

Download the single universal binary for your platform, add it to your PATH, and you're ready. Free to install and use.

Learn more
Linux x86_64
Intel / AMD 64-bit
Linux aarch64
ARM64
macOS
Apple Silicon
Windows x86_64
64-bit

Quick Install (Linux x86_64)

curl -LO https://downloads.devscriptor.com/installers/devscriptor-1.2.0-x86_64-unknown-linux-gnu.tar.gz tar -xzf devscriptor-1.2.0-x86_64-unknown-linux-gnu.tar.gz sudo mv devscriptor-*/devscriptor /usr/local/bin/
No dependencies for the core engine
4 GB RAM minimum (8 GB recommended)
Optional language runtimes only for LSP servers
MCP Server

Works With Your AI Coding Agents

Native MCP server with 74 total tools: 31 Core + 38 LSP + 5 Architecture

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31
Core Analysis
38
LSP Intelligence
5
Architecture

Core Analysis

scan_codebasesemantic_searchget_relationshipsadd_context_notefind_dead_codestart_watching

LSP Intelligence

get_hoverget_definitionget_referencesget_completionsget_call_hierarchyget_diagnostics

Architecture

lsp_arch_detectlsp_arch_checklsp_arch_batch_checklsp_arch_statuslsp_arch_setup

Supported AI Agents

Claude Desktop
Native
Cline
Native
Cursor
Compatible
Any MCP Client
Compatible
Context Graph

AI Agents That Remember

Long-term memory system that persists knowledge across AI sessions with 9 structured note types

Learn more

Same SQLite Database

Notes live alongside the code graph in one local file, persisting across sessions and processes.

Linked to Code & Concepts

Attach notes to concrete entities and abstract concepts, then recall them by association later.

Keyword, Semantic & Hybrid Search

Retrieve notes by keyword, vector similarity, or RRF-fused hybrid search with type & priority filters.

9 Structured Note Types

Comprehensive knowledge capture for any scenario

adr
Architecture Decisions
standard
Coding Standards
optimization
Performance
failure
Failures & Mistakes
practice
Best Practices
reflection
Reflections
general
General Knowledge
file_description
File Descriptions
modification
Modification Records
Companion tool · Juggler v1.0.0

Meet Juggler

Kimi and GLM are among the strongest coding models available — and almost every agent reaches them through a generic OpenAI-compatible shim that quietly drops what makes them good. Juggler is the agent that doesn't.

Preserved Thinking

Reasoning carries across turns instead of being thrown away. Kimi spells it thinking.keep, GLM spells it clear_thinking — with inverted polarity. Juggler translates.

Devscriptor, auto-wired

Detects your Devscriptor install and registers all 74 MCP tools on first run. Zero configuration.

Open weights, on-prem

Kimi and GLM ship open weights. Point --base-url at your own server and the whole stack — model, index, agent — stays inside your perimeter.

terminal
# One binary, three providers
$ juggler --provider glm --yes
# Devscriptor: found, 74 tools ready
$ juggler doctor
Native RustKimi · GLM · OpenAI26 built-in toolsSub-agents & swarms
Security First

Your Code Never Leaves Your Machine

100% local processing. No telemetry. Built for proprietary codebases.

Learn more

Local-First Analysis

Scanning, indexing, and search make no network calls.

Single SQLite File

Your knowledge graph lives in one portable local file.

Air-gapped Ready

Runs fully offline once the model is cached.

No Telemetry

No analytics, no tracking, no phone-home.