Context7
Up-to-date docs for AI agents
Beschreibung vom Entwickler (englisches Original)
The context platform for AI agents: code search, team decisions, and grounded project context.
Diese drei werden nie zu einer Punktzahl zusammengefasst: Meinungen, Messungen und Beliebtheit sind verschiedene Dinge.
Für diesen Server haben wir noch keine Zusammenfassung in einfacher Sprache geschrieben. Unten stehen die Fakten, die wir aus der Registry gelesen haben.
Wähle die KI-App, die du nutzt, und kopiere die Einstellungen.
CONTEXTSTREAM_API_KEY, CONTEXTSTREAM_API_URLAls geheim markierte Werte sind Schlüssel zu deinem Konto. Gib sie nie weiter und füge sie nie in einen Chat ein.
Du brauchst
Welche App nutzt du?
Wähle oben deine App. Wir merken sie uns, damit der Button beim nächsten Mal „In … installieren“ anzeigt.
Funktioniert in Claude im Web, auf dem Desktop und auf dem Handy:
https://mcp.contextstream.io/mcpÖffne Claude Desktop → Settings → Developer → Edit Config und füge dies in claude_desktop_config.json ein
{
"mcpServers": {
"contextstream": {
"command": "npx",
"args": [
"-y",
"@contextstream/mcp-server"
],
"env": {
"CONTEXTSTREAM_API_KEY": "your-value",
"CONTEXTSTREAM_API_URL": "your-value"
}
}
}
}Führe das in deinem Terminal aus
claude mcp add --transport http contextstream https://mcp.contextstream.io/mcpclaude mcp add contextstream --env CONTEXTSTREAM_API_KEY=your-value --env CONTEXTSTREAM_API_URL=your-value -- npx -y @contextstream/mcp-serverTrag die leeren Werte ein, bevor du ihn startest.
In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"contextstream": {
"url": "https://mcp.contextstream.io/mcp"
}
}
}In .cursor/mcp.json in deinem Projekt oder in ~/.cursor/mcp.json einfügen
{
"mcpServers": {
"contextstream": {
"command": "npx",
"args": [
"-y",
"@contextstream/mcp-server"
],
"env": {
"CONTEXTSTREAM_API_KEY": "your-value",
"CONTEXTSTREAM_API_URL": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"contextstream": {
"type": "http",
"url": "https://mcp.contextstream.io/mcp"
}
}
}In .vscode/mcp.json in deinem Projekt einfügen
{
"servers": {
"contextstream": {
"type": "stdio",
"command": "npx",
"args": [
"-y",
"@contextstream/mcp-server"
],
"env": {
"CONTEXTSTREAM_API_KEY": "your-value",
"CONTEXTSTREAM_API_URL": "your-value"
}
}
}
}Dein Browser fragt, ob er die App öffnen darf, dann zeigt die App die Einstellungen und bittet dich um Bestätigung. Schlüsselwerte bleiben leer, damit du sie selbst einträgst.
ChatGPT verbindet sich nur mit Servern im Internet:
https://mcp.contextstream.io/mcpMenünamen können sich je nach Tarif und mit der Zeit leicht unterscheiden.
Deine Auswahl bleibt in einem Cookie auf diesem Gerät; kein Konto nötig.
CONTEXTSTREAM_API_URL envDiese Einstellungen werden aus dem Registry-Eintrag des Entwicklers erzeugt. Wenn in der README etwas anderes steht, folge der README.
Der Server verlangt eine Anmeldung, bevor er seine Tools auflistet.
Wir prüfen Informationen, die jeder sehen kann; den Code haben wir nicht gelesen. Checks, die nicht zutreffen, werden nicht mitgezählt. · Geprüft am 6. Nov. 2026
Der Registry-Name wurde mit dem GitHub-Konto contextstream bestätigt, dem das Repo gehört
Dieses Repo haben wir noch nicht von GitHub gelesen
Dieses Repo haben wir noch nicht von GitHub gelesen
Antwort in 309 ms (HTTP 401)
Gibt OAuth-Anmeldung an, damit deine KI-App dich zum Einloggen weiterleiten kann
Noch nicht geprüft; wir lesen die Tool-Liste, wenn wir den Endpunkt prüfen
Verglichen mit allen aktiven Servern dieser Kategorie in der Registry. Sterne zählen nur, wenn dem Herausgeber das Repo gehört.
Er hat 3 von 3 zutreffenden Basischecks bestanden. Den Code haben wir nicht gelesen. Bevor du einen Schlüssel oder Token hinzufügst, sieh nach, welche Zugriffe der Server verlangt, und nutze einen Schlüssel, der nur die Berechtigungen hat, die du brauchst.
Das musst du eintragen: CONTEXTSTREAM_API_KEY
Beides geht: Installiere ihn auf deinem Computer oder verbinde dich mit der Cloud-Version.
Das GitHub-Repo wurde zuletzt – geändert, und die neueste Version (1.0.70) kam heute in die Registry.
Apps, die MCP unterstützen, etwa Claude Desktop, Claude Code, Cursor und VS Code. Er verbindet sich per URL, also funktionieren auch Apps, die Remote-MCP-Server akzeptieren, zum Beispiel ChatGPT im Entwicklermodus.
In derselben Kategorie: Context7, Codebase Memory, Exa
Server derselben Kategorie von anderen Entwicklern, sortiert nach Sternen.
So liest du eine Karte:★ GitHub-SterneiDrei Säulen: Bewertungen · Checks · NutzungiAktualisiert = neueste Version in der Registry veröffentlichti
Up-to-date docs for AI agents
Codebase knowledge graph for AI agents — 162 languages, sub-ms queries, 99% fewer tokens.
Connect AI agents to Exa for web search, content fetching, and multi-step research.
Unverändert aus dem Repo des Entwicklers übernommen. PopNx MCP hat den Inhalt weder geprüft noch empfiehlt es ihn. HTML, Bilder und Skripte wurden entfernt. Links führen von dieser Website weg.
ContextStream MCP Server
The context platform for AI agents.
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.
The numbers, their sources, and what they do not claim are under Benchmarks.
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?
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.
Each benchmark runs through the production API, is registered before its results are read, and is published with its method, confidence interval, and losses.
| Benchmark | ContextStream | Compared with |
|---|---|---|
| LongMemEval-S, all 500 questions | 96.8% (484/500); 96.0% on the half held out from tuning | Above Mastra (94.87%) and supermemory (85.4%) on the same official GPT-4o judge. Level with agentmemory's self-reported 96.2%, which is inside our 95% interval |
| LoCoMo, all 1,540 questions | 95.7% (1474/1540); 95.8% held out; 97.8% on the audited answer key | Above every system in the EverMemOS paper's same-judge table: EverMemOS 93.05%, Zep 85.22%, MemOS 80.76%, MemU 66.67%, Mem0 64.20% |
| Code search, 177 judged developer queries | 98.77% best answer in the top 10; 100% a useful file in the top 10 | Embedding-only search 72.84% and ripgrep 42.59% on the same queries and judgments |
| Agent tasks, 8 tasks × 3 trials | 23/24 passed (96%); 9/9 on tasks that need team knowledge | 14/24 (58%) and 0/9 with the repository alone |
61 ms median server-side search time (127 ms p95) in the October 27 production run. End to end it was 223 ms, because the client ran in a different region from the one serving the workspace. Your latency depends on your distance from that region.
Competitor figures are as each vendor or the EverMemOS paper published them; we did not re-run them, and readers and judges differ across rows. The code-search baselines come from the August 1 run on the same queries. The agent-task result uses one repository and one agent model, so treat it as directional. Results, methodology, and limitations.
For people ContextStream Create offers one-prompt making to, the server adds one tool, studio: ask for a film, a product explainer filmed from your connected product, an image, sound or music in plain words, and ContextStudio's producer plans the pieces from what your team knows (brand kit, docs, decisions, connected products). There are no models to pick.
form, with sizes (up to 6, such as instagram-post or linkedin-post) or a voice, and the plan keeps to it.plan returns the pieces and one price ("up to N credits, likely about M") and spends nothing. Pass what your agent knows that the workspace may not (the diff it just made, release notes, the doc it has open) as context; the producer reads it next to the team's own context.make spends at most the plan's price, and only after you agree: a client that can ask you (MCP elicitation, or a stateless input_required result) asks you itself; otherwise the agent passes the price you accepted.status reports each piece while it waits (with notifications/progress where the call asks for them); a product film takes 13 to 21 minutes. result shows images inline and links video and sound (signed links valid about 15 minutes), with each piece's placard. Brand work comes as files, each with its own link: every size as PNG, JPG and WebP with a ZIP of the set, a print PDF, or WAV and MP3 for the web with a broadcast master and stems, plus alt text, a caption and the checks it was held to.revise starts from a made image or sound: a variation (more like it), a revision (it, changed as you say) or a resize (an image in new sizes). Also stop, library, brand and products.email_draft writes one in your brand from a prompt ("announce our winter sale to customers") and sends nothing; email_audiences, email_campaigns, email_test (to your own address or Resend's test addresses), email_cancel and email_report (a campaign's delivery, opens, clicks, bounces and complaints, or the workspace's trends). email_send goes only with your go: the client asks you when it can; otherwise the agent shows you the campaign and its recipient count and passes the count you agreed to. email_preview gives a link to share that shows the email in Gmail, Outlook and Apple Mail mockups (desktop, tablet and phone, light and dark, images on or off), with the inbox line and what to check. email_revise changes a draft from plain words ("shorter subject") or sets its subject and preview line; email_duplicate makes a draft copy. email_contacts lists, adds (with where they agreed to hear from you) or unsubscribes contacts; erasing one can't be undone, so it is the delete tool's (studio.email_contact_erase), after your go; email_unsubscribes shows the suppression list with why and when, and takes an address off it only with your go. Resend is connected in the studio, never through an agent: the tool refuses anything shaped like a Resend key./studio serves only this tool, for Claude.ai or ChatGPT connectors, with OAuth tokens bound to that resource (read:studio, write:studio).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
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.
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.
contextstream-mcp setup --dry-run
contextstream-mcp doctor contextstream-mcp doctor --repair
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= --project-path=.
A hook for Claude Code and Cursor that checks the packages an install command names against their public registry before the command runs. It covers npm, pnpm, yarn, bun, npx, pip, uv, uvx, pipx, poetry and cargo, including claude mcp add ... -- npx ....
It skips projects and commands that use a private registry (.npmrc, pip.conf, uv or poetry sources, --registry, --index-url). CONTEXTSTREAM_PACKAGE_BOUNCER=off turns it off.
Claude Code: add this entry to PreToolUse in ~/.claude/settings.json, next to the hooks setup installed. update-hooks leaves it alone.
{ "matcher": "Bash", "hooks": [{ "type": "command", "command": "contextstream-mcp hook package-bouncer", "timeout": 8 }] }
Cursor (~/.cursor/hooks.json):
{ "version": 1, "hooks": { "beforeShellExecution": [{ "command": "contextstream-mcp hook package-bouncer" }] } }
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 g
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