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ContextStream
$19Starting price
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About ContextStream
ContextStream is a shared project memory tool built for both humans and AI agents collaborating on coding projects. It records insights, decisions, and context from ongoing work and stores them as reusable memory that can be referenced in future AI coding sessions. The system is designed to maintain continuity and context retention across AI-assisted development workflows, reducing redundant explanations and improving efficiency. ContextStream benchmarks competitively against other memory systems, achieving a 90.0% score on the LongMemEval-S benchmark, placing it within statistical parity of top-ranked systems like Zep. It supports seamless integration into existing development environments, enabling teams to build on prior knowledge without starting from scratch. The tool is particularly useful for teams working with AI agents, as it provides a persistent memory layer that enhances collaboration and reduces context loss between sessions.
Key features
- Captures and stores project insights as reusable memory
- Supports both human and AI agent collaboration
- Benchmarks at 90.0% on LongMemEval-S
- Maintains continuity across AI coding sessions
- Reduces redundant explanations and context loss
- Designed for seamless integration into development workflows
- Shared project memory for teams
- Competitive performance against top memory systems
Use cases
- AI-assisted coding projects requiring persistent context
- Teams collaborating with AI agents on software development
- Reusing past project learnings to avoid repeating work
Pros
- Achieves 90.0% on the LongMemEval-S benchmark, statistically matching top systems like Zep
- Demonstrates 99.38% recall@10 for useful code retrieval and 93.83% for best-answer files
- Improves agent task success rates from 14/24 to 23/24 in controlled tests with the same agent and repository
- Supports seamless integration across multiple AI coding environments via MCP protocol
- Provides persistent, scoped project memory that persists across sessions, tools, and agents
Cons
- Requires setup and configuration to capture and structure project context effectively
- Performance depends on the quality and completeness of captured project knowledge
- May introduce additional complexity for teams unfamiliar with shared memory systems
Frequently asked questions about ContextStream
What does ContextStream do?
ContextStream is a shared project memory tool that captures, stores, and surfaces project context—such as decisions, fixes, and dependencies—across AI agents and human collaborators. It enables agents to start sessions with relevant project knowledge, reducing redundant explanations and improving task success rates.
Who is ContextStream designed for?
ContextStream is designed for development teams and AI agents working on coding projects. It suits teams that rely on AI assistance and need to maintain continuity across sessions, tools, and personnel changes, such as onboarding new team members or switching between AI coding environments.
How does ContextStream integrate with existing workflows?
ContextStream integrates with popular AI coding tools like Claude Code, Cursor, Codex, Cline, and Windsurf via the MCP protocol. It captures context automatically during work and makes it available at the start of each new session or agent interaction.
What are the pricing tiers for ContextStream?
ContextStream offers a free Starter plan with 3,000 Context Credits per month. Paid plans include Pro ($19/month), Elite ($49/month), and Team ($79/user/month for teams of 3 or more), each with increasing context storage and features.
Can ContextStream be used with multiple AI agents?
Yes, ContextStream is designed to work with multiple AI agents. It provides a shared memory layer that allows different agents to access the same project context, reducing the need to re-explain the project or decisions between sessions.
How does ContextStream capture project context?
ContextStream captures context automatically as teams work, including decisions, fixes, corrections, and dependencies. It scopes this information to the relevant repository and makes it available in future sessions or agent interactions without manual documentation.
ContextStream Website Engagement
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