ContextStream
Persistent memory and cross-session learning for AI coding assistants (hosted remote MCP).
Install
Add this to your client's MCP configuration (Claude Desktop: claude_desktop_config.json; Cursor: .cursor/mcp.json; VS Code and others use the same "mcpServers" shape).
claude mcp add --transport http contextstream 'https://mcp.contextstream.io/mcp?default_context_mode=fast&src=registry'
{
"mcpServers": {
"contextstream": {
"type": "http",
"url": "https://mcp.contextstream.io/mcp?default_context_mode=fast&src=registry"
}
}
}
Documentation
From the project's README on GitHub, refreshed weekly. Links open on GitHub.
Contents
ContextStream MCP Server
Persistent memory. Millisecond code search.
Your agent knows code. Give it the decisions behind yours.
Connect your code, docs, and conversations so your agents can find the right files, recall saved decisions, and build on past work across sessions and tools.
Start free with MCP
10,000 monthly credits. No credit card required.
Works with Claude Code, Cursor, Codex, GitHub Copilot, Gemini CLI, Qwen Code, Kimi Code, Muse Code, ZCode, Zed, and more MCP clients, on Claude, GPT, Gemini, Kimi, GLM, Qwen, and other models. Create your account or sign in during MCP onboarding. No separate website signup needed.
macOS and Linux
curl -fsSL https://contextstream.io/scripts/mcp.sh | bash
Windows PowerShell
irm https://contextstream.io/scripts/mcp.ps1 | iex
Paste the command into your terminal and follow onboarding to connect your project and supported editor. Restart your editor after setup.
What gets installed and indexed? · Supported clients · Setup guide · Prefer to start on the web?
Make the next session useful
Ask your connected agent:
Use ContextStream to find the files relevant to my next change. Cite the sources and retrieve any saved project decisions that should guide the work.
Then ask it to save a real decision and its reason. Start a new session and retrieve that decision without explaining it again. Indexing supplies code context; it cannot recover every undocumented decision.
Proof and data controls
95 ms median code search in our published benchmark. This is the measured successful-response median for the disclosed configuration, not a latency guarantee. See results, methodology, and limitations.
Scoped access. Traceable sources. Configurable capture. Indexing sends eligible source contents to ContextStream for hosted search. Transcript saving and local Git metadata capture are on by default and can be turned off. Review data handling and controls before connecting sensitive projects.
Other installation options and troubleshooting
npm (Node.js 20+)
npx -y @contextstream/mcp-server@latest setup
The npm launcher downloads the native Rust binary for your platform and verifies its SHA-256 checksum. Pin an exact package version for production automation.
Hosted MCP without a local process
For clients supporting Streamable HTTP and OAuth, the hosted endpoint is:
https://mcp.contextstream.io/mcp?default_context_mode=fast
Supported clients lists one-line add commands for Claude Code, Codex, Gemini CLI, Qwen Code, Copilot CLI, and Droid, and one-click install for VS Code. Use the MCP documentation for other clients and stdio alternatives. A hosted connection alone does not sync your local checkout.
Preview or diagnose setup
contextstream-mcp setup --dry-run
contextstream-mcp doctor --scope=all --only-configured
Scripted and CI setup
For automation, wrap the install in pipefail so it fails when the download
fails, instead of reporting success after installing nothing:
bash -o pipefail -c 'curl -fsSL https://contextstream.io/scripts/mcp.sh | bash'
setup --yes reads the key from CONTEXTSTREAM_API_KEY or saved credentials,
and needs --workspace-id when the account has more than one workspace:
export CONTEXTSTREAM_API_KEY=... # or: printf %s "$KEY" | contextstream-mcp configure --api-key-stdin
contextstream-mcp setup --yes --editors=claude --workspace-id=<UUID> --project-path=.
Open source and contributing
This repository contains the MIT-licensed Rust MCP server, client, editor setup, and release tooling. The hosted backend is separate and is not included here. See the architecture, release integrity, and latest release.
cargo build --locked -p mcp-server --bin contextstream-mcp
cargo test --locked --workspace
Use the pinned Rust toolchain. For contribution checks and commit sign-off, read CONTRIBUTING.md. Report vulnerabilities using SECURITY.md. See LICENSE, NOTICE, and GOVERNANCE.md for licensing, trademarks, and project governance.
Let humans be human.
Docs · Pricing · Integrations · Benchmarks
Optional deep project learning
Deep project learning starts off for new accounts. Plain contextstream-mcp setup --yes
preserves your current choice. To review consent, run
contextstream-mcp configure --account-learning on and confirm on the signed-in
privacy page. To withdraw, run contextstream-mcp configure --account-learning off.
Agents cannot consent for you. Doctor and init show status only. See
data handling and controls.
Frequently asked questions
What is ContextStream?
Persistent memory and cross-session learning for AI coding assistants (hosted remote MCP).
How do I install ContextStream?
It runs as a remote server. In Claude Code: claude mcp add --transport http contextstream 'https://mcp.contextstream.io/mcp?default_context_mode=fast&src=registry'. For other clients, paste the JSON configuration from this page into their MCP settings.
Does ContextStream need an API key?
Its registry entry lists no required key or secret. Some features may still need an account with the service it connects to.
Is ContextStream open source?
Yes. Its code is on GitHub under the MIT license.
Who maintains ContextStream?
It is published by contextstream. AI.tn lists it but does not maintain or endorse it.
From the official MCP Registry. Listing is not an endorsement: review a server's code and permissions before giving it access to your data.