Is Contextcore Mcp safe to use?

Contextcore Mcp has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under AGPL-3.0.

How do I install Contextcore Mcp?

Contextcore Mcp supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.

What AI clients work with Contextcore Mcp?

Contextcore Mcp is compatible with Claude Desktop, Cursor, Claude Code, and most MCP clients that support stdio transport. It uses stdio and http transport.

Is Contextcore Mcp actively maintained?

Contextcore Mcp is actively maintained — last commit was 2 days ago. It has 14 GitHub stars.

Contextcore Mcp

ContextCore: An MCP server for Claude (or any AI tool) that enables massive token saving through hybrid search (BM25 + Embeddings)

ActiveNot tested

AI / ML

★ 14PyPI GitHub

61BNo CVEsactiveAGPL-3.0

Quick Install

{
  "mcpServers": {
    "contextcore": {
      "cwd": "C:\\Users\\USER\\Documents\\SDKSearchImplementation\\SearchEmbedSDK",
      "env": {
        "CONTEXTCORE_API_BASE_URL": "http://127.0.0.1:8000",
        "CONTEXTCORE_MCP_TIMEOUT_SECONDS": "120"
      },
      "args": [
        "C:\\Users\\USER\\Documents\\SDKSearchImplementation\\SearchEmbedSDK\\mcp_server.py"
      ],
      "command": "C:\\Users\\USER\\Documents\\SDKSearchImplementation\\SearchEmbedSDK\\.venv\\Scripts\\python.exe"
    }
  }
}

Setup guide

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Should you use this server?

> One MCP server for all your local files. Search everything, send only what matters to AI.

✓

Is it safe?

No known CVEs for contextcore.

No authentication — any process on your machine can connect.

AGPL-3.0. View license →

✓

Is it maintained?

Last commit 2 days ago. 14 stars.

Will it work with my client?

Transport: stdio, http. Works with Claude Desktop, Cursor, Claude Code, and most MCP clients.

README

ContextCore

One MCP server for all your local files. Search everything, send only what matters to AI.

Stop pasting entire files into Claude. ContextCore indexes your notes, code, documents, images, audio, and video locally — then exposes a single MCP server that any AI tool can query. Instead of bloating your context window, Claude searches first and retrieves only the relevant chunks.

57% fewer tokens. Same answers. No cloud.

Benchmark Setup	Baseline Context	ContextCore Context	Reduction
SciFact (top-5 retrieved docs vs chunked context)	1,723.5 tokens/query	733.4 tokens/query	57.45%

Works with: Claude Desktop · Claude Code · Cursor · Cline · OpenCode · any MCP-compatible tool

Why ContextCore?

Most developers working across large codebases or document collections hit the same wall: pasting everything into context is expensive, slow, and hits limits. RAG pipelines require infrastructure. Other memory tools are cloud-only or single-format.

ContextCore is a local-first MCP server that does hybrid search (BM25 + embeddings) across every file type you care about — and registers itself with your AI tools automatically. One install. One server. All your data.

It is not Supermemory. It does not sync to a cloud. Your files stay on your machine. What it gives you is supercharged retrieval across every local file format, surfaced directly inside Claude and other tools via MCP.

This is the one MCP to rule them all design: instead of managing separate MCP servers for different file types, you have one local server with a consistent search API across text, code, images, audio, and video.

How It Works

contextcore init — indexes your chosen folders (text, code, images, audio, video)
Registers as an MCP server with Claude Desktop, Claude Code, Cursor, or Cline
When you ask Claude about your files, ContextCore intercepts with a search tool call
Only the top matching chunks are injected into context — not the whole file

The hybrid search combines BM25 (keyword) and embeddings (semantic) so it handles both exact lookups ("find the function called parse_config") and fuzzy concept searches ("where did I write about the retry logic?").

Install

Install from PyPI:

python -m pip install contextcore

Optional source install (for contributors):

git clone https://github.com/lucifer-ux/SearchEmbedSDK.git
cd SearchEmbedSDK
python -m pip install -e .

Then run the setup wizard:

contextcore init

Gif is sped up to skip the installation parts.

That's it. ContextCore indexes your files, registers with your AI tools, and runs in the background. No config files to edit.

Prerequisites

Python 3.10+
Windows, macOS, or Linux
Internet access for first-time model downloads
Enough disk space for Python packages and model files

Optional but important:

ffmpeg for video indexing
Claude Desktop or another MCP-capable tool if you want interactive AI integration

What ContextCore Does

ContextCore gives you:

a CLI command: contextcore
a local backend server, normally on http://127.0.0.1:8000
an MCP server script for Claude and similar tools
local indexing for:
- text and documents
- images
- audio transcripts
- video embeddings and video context
- codebase context (structure, symbols, dependencies, file-level detail)

Codebase Context for Claude/OpenCode

ContextCore can expose your co

... View full README on GitHub

Test This Server

This server supports HTTP transport. Be the first to test it — help the community know if it works.

Score Breakdown

MCPpedia Score

Click each category to see evidence

61B

Last scored 7h ago

How we score →

Security

23/30

No known vulnerabilities.

✓

Known CVEs — No known CVEs for contextcorecheck OSV.dev

○

Tool safety — No tools to analyze

○

Tool poisoning — No tools to analyze

○

Injection vectors — No tools to analyze

✓

Tool stability — Tool definitions stable

○

Dependency health — found on deps.dev, recently updated

✓

License — License: AGPL-3.0

○

Authentication — No authentication required

○

Repository — active repo

CVEs checked daily via OSV.dev. Score algorithm is open source.

Reviews

Have you used this server?

Share your experience — it helps other developers decide.

How easy was setup?Did it work reliably?How was the documentation?

Frequently Asked Questions

Is Contextcore Mcp safe to use?: Contextcore Mcp has no known CVEs as of the latest MCPpedia security scan. It does not require authentication, so any local process can connect — keep this in mind in shared environments. Licensed under AGPL-3.0.
How do I install Contextcore Mcp?: Contextcore Mcp supports copy-paste install configs on its MCPpedia page for Claude Desktop, Cursor, and Claude Code. Scroll to the Quick Install section and select your client.
What AI clients work with Contextcore Mcp?: Contextcore Mcp is compatible with Claude Desktop, Cursor, Claude Code, and most MCP clients that support stdio transport. It uses stdio and http transport.
Is Contextcore Mcp actively maintained?: Contextcore Mcp is actively maintained — last commit was 2 days ago. It has 14 GitHub stars.

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Discussion

Start a conversation

Ask a question, share a tip, or report an issue.

Has anyone used this with Cursor?How do you handle auth?Any alternatives?

ContextCore

One MCP server for all your local files. Search everything, send only what matters to AI.

57% fewer tokens. Same answers. No cloud.

Benchmark Setup	Baseline Context	ContextCore Context	Reduction
SciFact (top-5 retrieved docs vs chunked context)	1,723.5 tokens/query	733.4 tokens/query	57.45%

Works with: Claude Desktop · Claude Code · Cursor · Cline · OpenCode · any MCP-compatible tool

Why ContextCore?

How It Works

contextcore init — indexes your chosen folders (text, code, images, audio, video)
Registers as an MCP server with Claude Desktop, Claude Code, Cursor, or Cline
When you ask Claude about your files, ContextCore intercepts with a search tool call
Only the top matching chunks are injected into context — not the whole file

Install

Install from PyPI:

python -m pip install contextcore

Optional source install (for contributors):

git clone https://github.com/lucifer-ux/SearchEmbedSDK.git
cd SearchEmbedSDK
python -m pip install -e .

Then run the setup wizard:

contextcore init

Gif is sped up to skip the installation parts.

That's it. ContextCore indexes your files, registers with your AI tools, and runs in the background. No config files to edit.

Prerequisites

Python 3.10+
Windows, macOS, or Linux
Internet access for first-time model downloads
Enough disk space for Python packages and model files

Optional but important:

ffmpeg for video indexing
Claude Desktop or another MCP-capable tool if you want interactive AI integration

What ContextCore Does

ContextCore gives you:

a CLI command: contextcore
a local backend server, normally on http://127.0.0.1:8000
an MCP server script for Claude and similar tools
local indexing for:
- text and documents
- images
- audio transcripts
- video embeddings and video context
- codebase context (structure, symbols, dependencies, file-level detail)

Codebase Context for Claude/OpenCode

ContextCore can expose your co

... View full README on GitHub