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jscpd MCP Server

Copy-paste detection MCP server that scans a codebase and lets AI assistants check snippets, inspect duplication statistics, and review current-directory duplication through jscpd's detection engine.

by Andrey Kucherenko · submitted by oktofeesh1·added 2026-06-06·
Claude CodeClaude Desktop
HarnessClaude CodeClaude Desktop
Review first — review before installing

Open the source and read safety notes before installing.

Citation facts

Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.

Canonical URL
https://heyclau.de/entry/mcp/jscpd-mcp-server
Source URLs
https://github.com/kucherenko/jscpd/blob/master/apps/jscpd-server/README.md, https://github.com/kucherenko/jscpd
Brand
jscpd
Brand domain
jscpd.dev
Brand asset source
brandfetch
Safety notes
jscpd-server scans the configured project directory on startup and can compare submitted snippets against the scanned codebase., The MCP server exposes duplication checks and statistics over an HTTP server that currently does not require authentication., Bind the server to local interfaces for personal workflows and avoid exposing scanned proprietary codebases to untrusted networks., Persistent stores such as LevelDB may retain codebase token/index data between runs., Snippet checks can reveal copied code fragments, file paths, line ranges, and duplication percentages to the MCP client and model.
Privacy notes
Source paths, snippets, duplicated fragments, clone locations, statistics, file formats, and project structure may be exposed through MCP tool results., Codebases may contain proprietary logic, credentials, customer identifiers, comments, internal APIs, security-sensitive code, or generated files., Reports and server logs can retain duplication evidence and scanned project metadata., Tune ignore rules before scanning vendored dependencies, generated files, test fixtures, secrets, or third-party code you do not want in model context.
Author
Andrey Kucherenko
Submitted by
oktofeesh1
Claim status
unclaimed
Last verified
2026-06-06

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Compare context
Selected

0

Current score

63

Baseline

—

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Needs review

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    Done

  • Source provenance statusRequired

    Marked as source-backed.

    Done

  • Metadata reviewed

    No reviewed flag detected in metadata.

    Pending

Safety and privacy checks

Complete

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    Review the listed safety guidance before running commands.

    Done

  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done

  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done

  • Package verification flag

    No package verification flag provided.

    Pending

  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending

  • Baseline comparison available

    No baseline peer selected yet.

    Pending

  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

CLI install

Copy-ready — paste the snippet to get started.

10 minutes

Install command

Provided

Config snippet

Provided

Copy snippet

Provided

Prerequisites

5 to clear

Platforms

2 listed

Install type

CLI install

Adoption plan

Balanced adoption plan

Current risk score 24/100. Use staged verification before broader rollout.

Risk 24

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done

  • Confirm metadata review state

    No review metadata found; increase manual validation.

    Pending

  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes are present.

    Done

  • Review privacy notesRequired

    Privacy notes are present.

    Done

  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending

  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending

  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Metadata review. Risk score 31.

Risk 31

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Missing

Review metadata is missing.

Required in this preset

Safety notes

Present

Safety notes are present.

Required in this preset

Privacy notes

Present

Privacy notes are present.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Metadata review

Decision timeline

Decision timeline · balanced

Blocking gaps: Check metadata review status. Risk 28.

Risk 28

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is missing.

Pending

verify

Review safety notesRequired

Safety notes are available.

Done

verify

Review privacy notes

Privacy notes are available.

Done

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Check metadata review status

Prerequisite readiness

Prerequisite readiness

5 prerequisites to line up before setup. Have accounts and credentials ready first.

0/5 ready
Account & credentials1Install & runtime1Permissions & scopes1Network & hosting210 minutes

Safety & privacy surface

Safety & privacy surface

5 safety and 4 privacy notes across 4 risk areas. Review closely: credentials & tokens, network access.

4 areas
  • SafetyLocal filesjscpd-server scans the configured project directory on startup and can compare submitted snippets against the scanned codebase.
  • SafetyNetwork accessThe MCP server exposes duplication checks and statistics over an HTTP server that currently does not require authentication.
  • SafetyNetwork accessBind the server to local interfaces for personal workflows and avoid exposing scanned proprietary codebases to untrusted networks.
  • SafetyCredentials & tokensPersistent stores such as LevelDB may retain codebase token/index data between runs.
  • SafetyLocal filesSnippet checks can reveal copied code fragments, file paths, line ranges, and duplication percentages to the MCP client and model.
  • PrivacyLocal filesSource paths, snippets, duplicated fragments, clone locations, statistics, file formats, and project structure may be exposed through MCP tool results.
  • PrivacyCredentials & tokensCodebases may contain proprietary logic, credentials, customer identifiers, comments, internal APIs, security-sensitive code, or generated files.
  • PrivacyData retentionReports and server logs can retain duplication evidence and scanned project metadata.
  • PrivacyCredentials & tokensTune ignore rules before scanning vendored dependencies, generated files, test fixtures, secrets, or third-party code you do not want in model context.

Safety notes

  • jscpd-server scans the configured project directory on startup and can compare submitted snippets against the scanned codebase.
  • The MCP server exposes duplication checks and statistics over an HTTP server that currently does not require authentication.
  • Bind the server to local interfaces for personal workflows and avoid exposing scanned proprietary codebases to untrusted networks.
  • Persistent stores such as LevelDB may retain codebase token/index data between runs.
  • Snippet checks can reveal copied code fragments, file paths, line ranges, and duplication percentages to the MCP client and model.

Privacy notes

  • Source paths, snippets, duplicated fragments, clone locations, statistics, file formats, and project structure may be exposed through MCP tool results.
  • Codebases may contain proprietary logic, credentials, customer identifiers, comments, internal APIs, security-sensitive code, or generated files.
  • Reports and server logs can retain duplication evidence and scanned project metadata.
  • Tune ignore rules before scanning vendored dependencies, generated files, test fixtures, secrets, or third-party code you do not want in model context.

Prerequisites

  • Node.js and npm available for installing `jscpd-server`.
  • A project directory you are authorized to scan for code duplication.
  • MCP client with Streamable HTTP support.
  • Port, host, and store settings chosen before exposing the server outside local development.
  • `.jscpd.json`, ignore patterns, gitignore behavior, and min-token/min-line thresholds reviewed for the target codebase.

Schema details

Install type
cli
Troubleshooting
No
Source repository stats
Scope
Source repo
Collection metadata
Estimated setup
10 minutes
Difficulty
intermediate
Full copyable content
npm install -g jscpd-server
jscpd-server PROJECT_DIR

About this resource

Content

jscpd MCP Server exposes copy-paste detection to AI assistants through the jscpd-server package. The server scans a codebase, then provides MCP tools for checking snippets against that codebase, retrieving duplication statistics, and checking the current directory.

The MCP server is useful for refactoring workflows where Claude or another agent needs to determine whether new or selected code duplicates existing patterns before suggesting an extraction, consolidation, or cleanup.

Source Review

These sources were reviewed on 2026-06-06. Prefer the live repository, server README, package metadata, and npm registry metadata for current commands, server options, MCP endpoint behavior, supported tools, package names, and duplication detection capabilities.

Features

  • Start a project-scoped duplication server with jscpd-server PROJECT_DIR.
  • Expose a Streamable HTTP MCP endpoint from the local jscpd server.
  • Check submitted snippets against the scanned project.
  • Retrieve project duplication statistics.
  • Check duplication in the current directory.
  • Configure host, port, store, config file, format filters, ignore patterns, minimum lines, minimum tokens, max source size, and detection mode.
  • Use persistent storage for production-style runs.
  • Support more than 225 programming languages and document formats through jscpd's detection engine.

Installation

Install the server package:

npm install -g jscpd-server

Start it against a project directory:

jscpd-server PROJECT_DIR

Configure your MCP client to use Streamable HTTP and the local server's /mcp route. Keep the service bound to a trusted local interface unless you have a separate access-control layer.

Tools

  • check_duplication: check a submitted snippet against the scanned codebase.
  • get_statistics: return duplication statistics for the scanned project.
  • check_current_directory: run a current-directory duplication check.

Use Cases

  • Ask Claude whether a proposed helper duplicates existing project code.
  • Check selected snippets before accepting generated code.
  • Drive duplication-aware refactoring sessions.
  • Review project duplication statistics from an editor or agent workflow.
  • Gate cleanup tasks with concrete clone locations and percentages.
  • Pair with jscpd's AI reporter and skills for token-efficient refactoring workflows.

Safety and Privacy

Run jscpd-server only on directories the agent is allowed to inspect. The server can expose source paths, clone locations, snippets, duplicated fragments, and project-level statistics. For proprietary repos, bind locally, avoid shared networks, and tune ignore rules before the initial scan.

Persistent stores can retain scan data. Treat LevelDB stores, reports, server logs, and MCP transcripts as code-derived artifacts that may need the same handling as source code.

Duplicate Check

No kucherenko/jscpd entry, jscpd MCP entry, jscpd-server MCP entry, or matching source URL was found in content/mcp.

#code-quality#duplication#static-analysis#streamable-http#refactoring

Source citations

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[![Listed on HeyClaude](https://heyclau.de/badge/mcp/jscpd-mcp-server.svg)](https://heyclau.de/entry/mcp/jscpd-mcp-server)

How it compares

jscpd MCP Server side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

Field
jscpd logojscpd MCP Server

Copy-paste detection MCP server that scans a codebase and lets AI assistants check snippets, inspect duplication statistics, and review current-directory duplication through jscpd's detection engine.

Open dossier
Codebase Memory MCP Server

High-performance MCP server that indexes codebases into a persistent knowledge graph for structural search, call tracing, architecture summaries, dead-code detection, and cross-repo analysis.

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CodeDB logoCodeDB MCP Server

Code intelligence MCP server with a Zig core for local project indexing, structural outlines, symbol lookup, search, dependency graphs, snapshots, remote public-repo queries, and fallback edits.

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Context+ MCP Server

MCP server for semantic codebase intelligence, combining AST structure, embeddings, clustering, feature hubs, restore points, and memory graph tools.

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Next steps
Open dossierAPI JSONOpen LLMMCP feedOpen sourceNewsletterClaim listing
Open dossierAPI JSONOpen LLMMCP feedOpen sourceNewsletterClaim listing
Open dossierAPI JSONOpen LLMMCP feedOpen sourceNewsletterClaim listing
Open dossierAPI JSONOpen LLMMCP feedOpen sourceNewsletterClaim listing
Trust
Review statusNot reviewedNot reviewedNot reviewedNot reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
Submitteroktofeesh1oktofeesh1oktofeesh1oktofeesh1
Install riskReview firstReview firstReview firstReview first
Notes Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓ Safety ✓ Privacy ✓
Brandjscpd logojscpd—CodeDB logoCodeDB—
Categorymcpmcpmcpmcp
SourceSource-backedSource-backedSource-backedSource-backed
AuthorAndrey KucherenkoDeusDatajustrachforloopcodes
Added2026-06-062026-06-052026-06-062026-06-05
Platforms
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Harness
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Claude CodeClaude Desktop
Source repo————
Safety notes✓jscpd-server scans the configured project directory on startup and can compare submitted snippets against the scanned codebase. The MCP server exposes duplication checks and statistics over an HTTP server that currently does not require authentication. Bind the server to local interfaces for personal workflows and avoid exposing scanned proprietary codebases to untrusted networks. Persistent stores such as LevelDB may retain codebase token/index data between runs. Snippet checks can reveal copied code fragments, file paths, line ranges, and duplication percentages to the MCP client and model.✓Codebase Memory MCP reads source files across indexed repositories and writes MCP entries, instruction files, skills, hooks, and agent configuration files during install. The background watcher and auto-index features can keep graph data updated as source files change. The optional graph UI exposes a local visualization server on a localhost port. Shared graph artifacts and SQLite databases can persist source metadata after an MCP session ends. Verify downloaded release binaries, checksums, signatures, and provenance before running them in sensitive environments.✓CodeDB indexes local projects and exposes file tree, outline, search, symbol, caller, dependency, read, snapshot, project, and context tools to the MCP client. CodeDB's `codedb_edit` tool exists as a fallback editing tool and can create, replace, insert, delete, or modify files when used by a client without native edit tooling. The npm package runs a postinstall step that downloads a native binary from GitHub Releases; review package and release provenance in environments that restrict native binaries. Remote repo queries use the public `api.wiki.codes` service and should be treated as network access outside the local repository. The upstream README marks the project as alpha software, with parser coverage and snapshot formats still stabilizing.✓Context+ can inspect source files, build AST and embedding indexes, run static analysis, create memory graph nodes, and propose code changes. The `propose_commit` tool is designed to write code after validation and creates shadow restore points before saving. Static analysis tools may invoke local compilers, linters, or language tools depending on the repository. Runtime caches and memory graph data can persist source-derived embeddings and relationships after the MCP session ends. External embedding providers can receive source-derived text, identifiers, prompts, and cluster-labeling context.
Privacy notes✓Source paths, snippets, duplicated fragments, clone locations, statistics, file formats, and project structure may be exposed through MCP tool results. Codebases may contain proprietary logic, credentials, customer identifiers, comments, internal APIs, security-sensitive code, or generated files. Reports and server logs can retain duplication evidence and scanned project metadata. Tune ignore rules before scanning vendored dependencies, generated files, test fixtures, secrets, or third-party code you do not want in model context.✓Source code, filenames, paths, symbols, comments, imports, routes, call graphs, architecture summaries, ADRs, graph queries, prompts, and tool outputs may be visible to the MCP client and model provider. Persistent graph databases and shared artifacts can retain proprietary architecture, internal package names, route names, service boundaries, and accidentally committed secrets. Auto-indexing broad workspace roots can include unrelated private repositories or generated files. Avoid committing shared graph artifacts unless the repository owners explicitly approve storing derived code intelligence in version control.✓Local indexes, snapshots, file trees, symbol names, dependency graphs, snippets, read results, and search results can reveal proprietary code structure and implementation details. Upstream documents sensitive-file blocking for patterns such as environment files, credentials, and keys, but users should still review ignore rules and avoid indexing secret-heavy directories. CodeDB writes telemetry to `~/.codedb/telemetry.ndjson` unless `CODEDB_NO_TELEMETRY=1` is set, then syncs aggregate tool counts, latency, startup, file count, line count, language, version, and platform data on MCP session close. Upstream telemetry docs state that source code, file contents, file paths, and search queries are not collected. Remote public-repo queries and local MCP responses may still be logged by MCP clients, model providers, and terminal history.✓Source code, file paths, symbol names, comments, identifiers, embeddings, memory nodes, relations, prompts, API keys, static-analysis output, proposed diffs, and tool results may be visible to the MCP client and model provider. Proprietary codebases can expose internal architecture, feature maps, naming conventions, secrets accidentally present in code, and product plans. Keep API keys and provider base URLs out of committed MCP configs, logs, screenshots, and shared prompts. Review `.mcp_data` and generated restore-point data before sharing workspaces or artifacts.
Prerequisites
  • Node.js and npm available for installing `jscpd-server`.
  • A project directory you are authorized to scan for code duplication.
  • MCP client with Streamable HTTP support.
  • Port, host, and store settings chosen before exposing the server outside local development.
  • A local repository or workspace you are authorized to index.
  • Platform-compatible Codebase Memory MCP release binary verified before use.
  • Agent configuration write access reviewed before running the installer.
  • Sensitive paths, generated files, vendored code, secrets, and private repositories reviewed before indexing.
  • macOS or Linux on x64 or arm64 for the published native binary launcher.
  • Node.js 18 or newer when using the `codedeebee` npm launcher.
  • A local project directory that the MCP client exposes through roots or launches from.
  • Review of which local repositories, file types, generated artifacts, and secrets patterns may be indexed.
  • Node.js and npx available to the MCP client runtime.
  • A repository or workspace you are authorized to index and expose to an MCP client.
  • Ollama embedding model available, or an approved OpenAI-compatible embedding provider and API key.
  • Static analysis tools installed if you want Context+ to run native linters or compilers.
Install
npm install -g jscpd-server && jscpd-server PROJECT_DIR
npm install -g codebase-memory-mcp
npx -y codedeebee mcp
npx -y contextplus
Config
Manual-only setup:
{
  "mcpServers": {
    "jscpd": {
      "type": "streamable-http",
      "url": "LOCAL_JSCPD_SERVER_MCP_URL"
    }
  }
}
{
  "mcpServers": {
    "codebase-memory": {
      "command": "npx",
      "args": ["-y", "codebase-memory-mcp"]
    }
  }
}
{
  "mcpServers": {
    "codedb": {
      "command": "npx",
      "args": [
        "-y",
        "codedeebee",
        "mcp"
      ],
      "type": "stdio"
    }
  }
}
{
  "mcpServers": {
    "contextplus": {
      "command": "npx",
      "args": ["-y", "contextplus"],
      "env": {
        "CONTEXTPLUS_EMBED_PROVIDER": "ollama",
        "OLLAMA_EMBED_MODEL": "nomic-embed-text",
        "OLLAMA_CHAT_MODEL": "llama3.2"
      }
    }
  }
}
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