typescript export/import graph analysis, symbol resolution and type checking, mcp server integration for llm context, batch file analysis and reporting, cli command-line interface with structured output, incremental compilation state management

ts-scan

CLI ToolFree

CLI/MCP tool providing TypeScript code intelligence via the TypeScript Language Service. Analyze exports, imports, resolve symbols, and check type errors.

Open Source

/ 100

6 capabilities

Capabilities6 decomposed

typescript export/import graph analysis

Medium confidence

Leverages the TypeScript Language Service to parse and analyze module dependency graphs, extracting all named exports, default exports, and import statements from TypeScript/JavaScript files. Uses the compiler API's SourceFile AST traversal to identify export declarations and their symbols, enabling precise mapping of what each module exposes and consumes without executing code.

Solves for

I need to understand what a TypeScript module exports so I can use it correctly in my codeI want to find all files that import a specific symbol to understand its usage patternsI need to detect unused exports or circular dependencies in my codebaseI'm refactoring and need to know the full dependency graph before moving files

Best for

TypeScript developers analyzing large codebases

Teams building code generation or scaffolding tools

Developers integrating code intelligence into LLM agents via MCP

Requires

Node.js 14+

TypeScript 4.0+ installed locally or as peer dependency

Valid tsconfig.json in project root or specified path

Limitations

Requires a valid TypeScript configuration (tsconfig.json) to resolve module paths correctly

Cannot analyze dynamic imports or require() calls with non-literal arguments

Performance degrades on very large monorepos (10k+ files) without proper caching strategy

What makes it unique

Uses TypeScript's official Language Service API (not a custom parser) to analyze exports/imports, ensuring 100% compatibility with TypeScript's own module resolution rules and type-aware symbol tracking, rather than regex or AST-walking approaches that miss edge cases like namespace exports or conditional exports

vs alternatives

More accurate than regex-based tools because it respects TypeScript's actual module resolution algorithm and handles complex patterns (namespace exports, re-exports, type-only imports) that simpler parsers miss

symbol resolution and type checking

Medium confidence

Integrates the TypeScript Language Service's symbol resolution engine to locate symbol definitions, trace their types, and report type errors at specific locations in code. Queries the compiler's getDefinitionAtPosition() and getQuickInfoAtPosition() APIs to resolve symbols to their declaration sites and retrieve type information without full compilation.

Solves for

I need to find where a symbol is defined so I can navigate to its sourceI want to check if my code has type errors before running itI need to understand the inferred type of a variable at a specific locationI'm building an IDE feature and need symbol information for autocomplete or hover tooltips

Best for

IDE/editor plugin developers needing language-aware features

LLM agents that need to understand code semantics for refactoring

CI/CD pipelines requiring fast type-checking without full compilation

Requires

TypeScript 4.0+

Valid tsconfig.json with proper module resolution settings

Source files must be accessible and syntactically valid

Limitations

Requires TypeScript to be installed in the project (cannot work with plain JavaScript without a jsconfig.json)

Type checking is incremental and may miss errors if source files are not properly tracked

Cannot resolve symbols across monorepo boundaries without proper path mapping in tsconfig.json

What makes it unique

Directly wraps TypeScript's Language Service APIs rather than reimplementing type-checking logic, meaning it inherits TypeScript's exact type inference rules and error reporting, and can be updated automatically when TypeScript releases new type features

vs alternatives

More reliable than custom type checkers because it uses the same type inference engine as tsc, eliminating discrepancies between what the tool reports and what TypeScript itself would report

mcp server integration for llm context

Medium confidence

Exposes TypeScript code intelligence capabilities as a Model Context Protocol (MCP) server, allowing LLM agents and Claude to query code structure, symbols, and type information through a standardized tool interface. Implements MCP resource and tool schemas that map code analysis operations to callable functions with structured input/output contracts.

Solves for

I want Claude to understand my TypeScript codebase so it can generate accurate code changesI need an LLM agent to resolve symbol definitions and type errors as part of a code refactoring workflowI'm building a multi-agent system where one agent needs to query another agent's code knowledgeI want to give my AI assistant read-only access to code intelligence without exposing the full codebase

Best for

Developers integrating Claude or other LLMs into TypeScript development workflows

Teams building AI-assisted code generation or refactoring agents

Organizations needing to expose code intelligence to LLMs with controlled access

Requires

Node.js 14+

TypeScript 4.0+

MCP client (Claude, custom agent, or MCP inspector)

Limitations

MCP server adds network/IPC overhead compared to direct API calls (typically 10-50ms per request)

LLM context window limits how much code metadata can be returned per query

Requires MCP client implementation on the LLM side (Claude, custom agents)

What makes it unique

Bridges TypeScript Language Service (a desktop/CLI tool) to the MCP protocol, enabling LLMs to access real-time code intelligence without embedding the entire TypeScript compiler in the LLM context, using a client-server architecture that keeps analysis on the developer's machine

vs alternatives

More efficient than sending full source code to an LLM because it only transmits structured metadata (exports, types, errors) rather than raw code, reducing token usage and enabling LLMs to work with larger codebases

batch file analysis and reporting

Medium confidence

Processes multiple TypeScript files in a single invocation, collecting exports, imports, type errors, and symbol information across the entire codebase or a specified subset. Aggregates results into a unified report format (JSON, text, or structured output) that can be piped to other tools or stored for further analysis.

Solves for

I need a report of all type errors in my project to prioritize fixesI want to export the full module dependency graph as JSON for visualization or analysisI need to audit all exports across my codebase to find unused or incorrectly typed onesI'm generating documentation and need to extract all public APIs from my TypeScript library

Best for

DevOps engineers building code quality gates in CI/CD pipelines

Documentation generators that need to extract API signatures

Teams auditing large codebases for type safety or API consistency

Requires

Node.js 14+

TypeScript 4.0+

Valid tsconfig.json

Limitations

Batch processing scales linearly with file count; 10k+ files may take minutes without parallelization

Output can be very large for big projects (megabytes of JSON); requires streaming or pagination for web tools

No built-in filtering or aggregation; consumers must post-process results to extract specific insights

What makes it unique

Aggregates TypeScript Language Service analysis across multiple files without re-initializing the compiler for each file, using a single LanguageServiceHost instance to maintain incremental compilation state and reduce memory overhead

vs alternatives

Faster than running tsc --noEmit for type checking because it only analyzes requested information (exports, errors) rather than performing full type inference and emit, making it suitable for quick CI/CD checks

cli command-line interface with structured output

Medium confidence

Provides a command-line interface that wraps TypeScript code intelligence operations, accepting file paths, symbols, and options as CLI arguments and outputting results in multiple formats (JSON, text, JSONL). Implements standard CLI patterns (exit codes, error messages, help text) and integrates with Unix pipes and shell scripting for composability.

Solves for

I want to run code analysis as part of a shell script or MakefileI need to pipe code analysis results to grep, jq, or other Unix tools for filteringI'm building a CI/CD pipeline and need a simple command to check for type errorsI want to integrate code intelligence into my editor or IDE via a subprocess call

Best for

DevOps engineers and SREs building shell-based automation

Developers using Unix/Linux development environments

Teams with existing CLI-based tooling pipelines

Requires

Node.js 14+ installed and in PATH

TypeScript 4.0+ installed locally

Bash or compatible shell (for piping)

Limitations

CLI startup overhead (Node.js process initialization) adds 100-500ms per invocation; not suitable for sub-second latency requirements

Output formatting is text-based; binary or streaming data requires additional encoding

No interactive mode; each invocation is stateless and cannot maintain context across commands

What makes it unique

Implements a thin CLI wrapper around the TypeScript Language Service that preserves the service's incremental compilation state across multiple CLI invocations when used as a daemon or long-running process, rather than reinitializing the compiler for each command

vs alternatives

More composable than tsc because it outputs structured data (JSON) by default and supports Unix pipes, making it easier to integrate into shell scripts and CI/CD pipelines without custom parsing

incremental compilation state management

Medium confidence

Maintains an in-memory Language Service instance that tracks file changes and reuses compilation state across multiple analysis queries, avoiding redundant parsing and type-checking of unchanged files. Uses TypeScript's incremental compilation APIs to update only affected files when the codebase changes.

Solves for

I'm running repeated code analysis queries and want to avoid recompiling the entire project each timeI need fast feedback when I save a file, without waiting for a full type-checkI'm building a long-running agent that analyzes code multiple times and needs responsive performanceI want to minimize CPU and memory usage when analyzing large projects

Best for

Developers building real-time code analysis tools (IDE plugins, watchers)

LLM agents that perform multiple code queries in a single session

CI/CD systems that run multiple checks on the same codebase

Requires

Node.js 14+ with sufficient heap memory (at least 512MB for medium projects)

TypeScript 4.0+

Valid tsconfig.json

Limitations

Incremental state is lost when the process exits; no persistent caching across restarts

Memory usage grows with project size and number of analyzed files; large projects may require periodic garbage collection

File watching and change detection must be implemented externally; ts-scan does not provide file system monitoring

What makes it unique

Leverages TypeScript's built-in incremental compilation APIs (getSourceFile caching, program reuse) rather than implementing custom caching, ensuring compatibility with TypeScript's own optimization strategies and reducing maintenance burden

vs alternatives

Faster than re-running tsc for each query because it reuses the compiler's internal state and only re-analyzes changed files, providing sub-second response times for repeated queries on large projects

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

Related Artifactssharing capabilities

Artifacts that share capabilities with ts-scan, ranked by overlap. Discovered automatically through the match graph.

MCP Server25

cls-mcp-server

[![npm version](https://img.shields.io/npm/v/cls-mcp-server)](https://www.npmjs.com/package/cls-mcp-server) [![license](https://img.shields.io/npm/l/cls-mcp-server)](https://github.com/Tencent/cls-mcp-server/blob/v1.0.2/LICENSE)

tool definition and schema-based function callingmcp server initialization and lifecycle management

2 shared capabilities

Framework23

@redocly/mcp-typescript-sdk

Model Context Protocol implementation for TypeScript

model context protocol server implementation with typescript bindingslogging and debugging support with structured output

2 shared capabilities

MCP Server31

@theia/ai-mcp-server

Theia - MCP Server

symbol definition and reference lookup via mcp

1 shared capability

CLI Tool22

mcp-lint

Lint MCP server tool schemas for cross-client compatibility + runtime preflight for agent tool calls

mcp server schema validation and linting

1 shared capability

MCP Server27

ECharts

** - Generate visual charts using [ECharts](https://echarts.apache.org) with AI MCP dynamically, used for chart generation and data analysis.

mcp-based chart generation tool registration and routing

1 shared capability

MCP Server21

@fractal-mcp/generate

TypeScript code generation from MCP server tool schemas

mcp server tool schema introspection and parsing

1 shared capability

Best For

✓TypeScript developers analyzing large codebases
✓Teams building code generation or scaffolding tools
✓Developers integrating code intelligence into LLM agents via MCP
✓IDE/editor plugin developers needing language-aware features
✓LLM agents that need to understand code semantics for refactoring
✓CI/CD pipelines requiring fast type-checking without full compilation
✓Code review tools that need to flag type errors programmatically
✓Developers integrating Claude or other LLMs into TypeScript development workflows

Known Limitations

⚠Requires a valid TypeScript configuration (tsconfig.json) to resolve module paths correctly
⚠Cannot analyze dynamic imports or require() calls with non-literal arguments
⚠Performance degrades on very large monorepos (10k+ files) without proper caching strategy
⚠Does not track re-exports across multiple module hops automatically
⚠Requires TypeScript to be installed in the project (cannot work with plain JavaScript without a jsconfig.json)
⚠Type checking is incremental and may miss errors if source files are not properly tracked

Requirements

Node.js 14+TypeScript 4.0+ installed locally or as peer dependencyValid tsconfig.json in project root or specified pathRead access to source filesTypeScript 4.0+Valid tsconfig.json with proper module resolution settingsSource files must be accessible and syntactically validMCP client (Claude, custom agent, or MCP inspector)

Input / Output

Accepts: TypeScript source files (.ts, .tsx), JavaScript files (.js, .jsx), tsconfig.json configuration, File path and position (line/column), TypeScript source code, tsconfig.json, MCP tool calls with JSON parameters, File paths and symbol names, Position coordinates (line/column), File glob patterns or directory paths, Configuration options (output format, filters), Command-line arguments (file paths, flags, options), stdin (for piped input, if supported), Configuration files (tsconfig.json), File paths and content (for updates), Query parameters (symbols, positions)

Produces: JSON structured export/import metadata, Symbol name arrays, Module path strings, Symbol definition location (file, line, column), Type information (string representation), Diagnostic error objects with location and message, JSON-serialized code metadata, Symbol definitions and type information, Diagnostic error reports, JSON report with exports, imports, errors, Plain text summary, Structured data (CSV, JSONL for streaming), JSON (stdout), Plain text (stdout), JSONL (newline-delimited JSON), Exit codes (0 for success, non-zero for errors), Analysis results (exports, types, errors), Incremental compilation diagnostics

UnfragileRank

Adoption13%(25% weight)

Quality27%(25% weight)

Ecosystem50%(10% weight)

Match Graph25%(35% weight)

Freshness75%(5% weight)

UnfragileRank is computed from adoption signals, documentation quality, ecosystem connectivity, match graph feedback, and freshness. No artifact can pay for a higher rank.

Type: CLI Tool

6 capabilities

Visit ts-scan→

Package Details

npm

Registry

0.1.5

Version

931

Weekly Downloads

About

CLI/MCP tool providing TypeScript code intelligence via the TypeScript Language Service. Analyze exports, imports, resolve symbols, and check type errors.

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Capabilities6 decomposed

typescript export/import graph analysis

Medium confidence

Solves for

Best for

TypeScript developers analyzing large codebases

Teams building code generation or scaffolding tools

Developers integrating code intelligence into LLM agents via MCP

Requires

Node.js 14+

TypeScript 4.0+ installed locally or as peer dependency

Valid tsconfig.json in project root or specified path

Limitations

Requires a valid TypeScript configuration (tsconfig.json) to resolve module paths correctly

Cannot analyze dynamic imports or require() calls with non-literal arguments

Performance degrades on very large monorepos (10k+ files) without proper caching strategy

What makes it unique

vs alternatives

symbol resolution and type checking

Medium confidence

Solves for

Best for

IDE/editor plugin developers needing language-aware features

LLM agents that need to understand code semantics for refactoring

CI/CD pipelines requiring fast type-checking without full compilation

Requires

TypeScript 4.0+

Valid tsconfig.json with proper module resolution settings

Source files must be accessible and syntactically valid

Limitations

Requires TypeScript to be installed in the project (cannot work with plain JavaScript without a jsconfig.json)

Type checking is incremental and may miss errors if source files are not properly tracked

Cannot resolve symbols across monorepo boundaries without proper path mapping in tsconfig.json

What makes it unique

vs alternatives

More reliable than custom type checkers because it uses the same type inference engine as tsc, eliminating discrepancies between what the tool reports and what TypeScript itself would report

mcp server integration for llm context

Medium confidence

Solves for

Best for

Developers integrating Claude or other LLMs into TypeScript development workflows

Teams building AI-assisted code generation or refactoring agents

Organizations needing to expose code intelligence to LLMs with controlled access

Requires

Node.js 14+

TypeScript 4.0+

MCP client (Claude, custom agent, or MCP inspector)

Limitations

MCP server adds network/IPC overhead compared to direct API calls (typically 10-50ms per request)

LLM context window limits how much code metadata can be returned per query

Requires MCP client implementation on the LLM side (Claude, custom agents)

What makes it unique

vs alternatives

batch file analysis and reporting

Medium confidence

Solves for

Best for

DevOps engineers building code quality gates in CI/CD pipelines

Documentation generators that need to extract API signatures

Teams auditing large codebases for type safety or API consistency

Requires

Node.js 14+

TypeScript 4.0+

Valid tsconfig.json

Limitations

Batch processing scales linearly with file count; 10k+ files may take minutes without parallelization

Output can be very large for big projects (megabytes of JSON); requires streaming or pagination for web tools

No built-in filtering or aggregation; consumers must post-process results to extract specific insights

What makes it unique

vs alternatives

cli command-line interface with structured output

Medium confidence

Solves for

Best for

DevOps engineers and SREs building shell-based automation

Developers using Unix/Linux development environments

Teams with existing CLI-based tooling pipelines

Requires

Node.js 14+ installed and in PATH

TypeScript 4.0+ installed locally

Bash or compatible shell (for piping)

Limitations

CLI startup overhead (Node.js process initialization) adds 100-500ms per invocation; not suitable for sub-second latency requirements

Output formatting is text-based; binary or streaming data requires additional encoding

No interactive mode; each invocation is stateless and cannot maintain context across commands

What makes it unique

vs alternatives

More composable than tsc because it outputs structured data (JSON) by default and supports Unix pipes, making it easier to integrate into shell scripts and CI/CD pipelines without custom parsing

incremental compilation state management

Medium confidence

Solves for

Best for

Developers building real-time code analysis tools (IDE plugins, watchers)

LLM agents that perform multiple code queries in a single session

CI/CD systems that run multiple checks on the same codebase

Requires

Node.js 14+ with sufficient heap memory (at least 512MB for medium projects)

TypeScript 4.0+

Valid tsconfig.json

Limitations

Incremental state is lost when the process exits; no persistent caching across restarts

Memory usage grows with project size and number of analyzed files; large projects may require periodic garbage collection

File watching and change detection must be implemented externally; ts-scan does not provide file system monitoring

What makes it unique

vs alternatives

Capabilities are decomposed by AI analysis. Each maps to specific user intents and improves with match feedback.

ts-scan

Capabilities6 decomposed

typescript export/import graph analysis

symbol resolution and type checking

mcp server integration for llm context

batch file analysis and reporting

cli command-line interface with structured output

incremental compilation state management

Related Artifactssharing capabilities

cls-mcp-server

@redocly/mcp-typescript-sdk

@theia/ai-mcp-server

mcp-lint

ECharts

@fractal-mcp/generate

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to ts-scan

Are you the builder of ts-scan?

Get the weekly brief

Data Sources

ts-scan

Capabilities6 decomposed

typescript export/import graph analysis

symbol resolution and type checking

mcp server integration for llm context

batch file analysis and reporting

cli command-line interface with structured output

incremental compilation state management

Related Artifactssharing capabilities

cls-mcp-server

@redocly/mcp-typescript-sdk

@theia/ai-mcp-server

mcp-lint

ECharts

@fractal-mcp/generate

Best For

Known Limitations

Requirements

Input / Output

UnfragileRank

Package Details

About

Categories

Alternatives to ts-scan

Are you the builder of ts-scan?

Get the weekly brief

Data Sources