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Implements MCP server specification with tool definitions, input validation, and response formatting, allowing seamless integration with Claude, custom agents, and other MCP-compatible clients without custom API wrappers.","intents":["Enable Claude to execute code as part of multi-turn conversations","Bind code execution to AI agent tool registries without custom integration code","Standardize how AI systems invoke external code execution capabilities","Build composable AI workflows that chain code execution with other MCP tools"],"best_for":["AI agent developers using Claude or other MCP-compatible LLMs","Teams building multi-tool AI systems with standardized tool interfaces","Developers integrating code execution into existing MCP server ecosystems"],"limitations":["MCP protocol overhead adds ~50-100ms per tool invocation","Tool schema validation may reject complex or dynamic input structures","Limited to MCP-compatible clients — no direct REST API exposure","Requires MCP server setup and configuration (though E2B provides pre-built server)"],"requires":["MCP-compatible client (Claude Desktop, custom MCP host, etc.)","E2B MCP server running (provided as open-source package)","E2B API key for authentication"],"input_types":["tool invocation with structured parameters","code snippets as string arguments","file references (URLs or base64-encoded content)"],"output_types":["structured tool response (JSON)","execution status and results","error messages with stack traces"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-e2b__cap_2","uri":"capability://code.generation.editing.multi.language.code.execution.with.language.specific.runtimes","name":"multi-language code execution with language-specific runtimes","description":"Provides pre-configured runtime environments for Python, JavaScript/Node.js, Bash, Go, Rust, and other languages within the same sandbox instance. Each language has its own package manager (pip, npm, cargo, etc.) and standard library pre-installed, allowing developers to execute polyglot scripts or switch languages mid-session without environment reconfiguration.","intents":["Execute Python data analysis scripts alongside Node.js API calls in a single workflow","Test code generated by LLMs across multiple languages without manual environment setup","Build language-agnostic code execution tools that auto-detect and run code in the appropriate runtime","Prototype cross-language integrations (e.g., Python ML model + Node.js API wrapper)"],"best_for":["Polyglot development teams using multiple languages in the same project","AI agent developers building language-agnostic code execution capabilities","Educational platforms teaching multiple programming languages"],"limitations":["Language runtimes share the same sandbox — no isolation between Python and Node.js processes","Package installation (pip install, npm install) adds latency (~5-30 seconds depending on package size)","Limited to pre-installed languages — custom runtime installation requires container image customization","Cross-language communication requires explicit file I/O or network calls (no shared memory)"],"requires":["E2B API key","Knowledge of target language syntax and standard library","Network connectivity for package downloads (pip, npm, etc.)"],"input_types":["Python code (3.8+)","JavaScript/Node.js code (14+)","Bash scripts","Go source files","Rust source files"],"output_types":["stdout/stderr from any language","exit codes","generated files in any format"],"categories":["code-generation-editing"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-e2b__cap_3","uri":"capability://data.processing.analysis.persistent.file.system.within.ephemeral.sandbox.sessions","name":"persistent file system within ephemeral sandbox sessions","description":"Provides a writable file system within each sandbox that persists across multiple code executions within the same session, allowing scripts to read/write files, create directories, and maintain state between runs. Files are isolated per sandbox instance and automatically cleaned up when the sandbox terminates, preventing data leakage between sessions.","intents":["Generate and manipulate files (CSV, JSON, images) across multiple code execution steps","Build multi-step workflows where one script generates output consumed by the next","Cache intermediate results (e.g., downloaded datasets) within a session to avoid re-downloading","Test file I/O operations and data pipelines in isolation"],"best_for":["Data processing workflows that generate intermediate artifacts","AI agents building multi-step code execution pipelines","Developers testing file-based integrations (CSV parsing, image processing, etc.)"],"limitations":["File system is ephemeral — data is lost when sandbox terminates (typically after 30 minutes of inactivity)","No built-in persistence layer — requires explicit export/download to store results permanently","Disk space is limited (typically 1-10 GB depending on plan) — large datasets may exceed quota","File access is synchronous — no async I/O optimization for large file operations"],"requires":["E2B API key","Code that explicitly writes to /tmp or home directory","Mechanism to download files before sandbox cleanup (API call or explicit export)"],"input_types":["file paths (relative or absolute)","file content (text or binary)","directory structures"],"output_types":["file artifacts (downloadable via API)","directory listings","file metadata (size, permissions)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-e2b__cap_4","uri":"capability://safety.moderation.resource.limited.execution.with.cpu.memory.and.timeout.constraints","name":"resource-limited execution with cpu, memory, and timeout constraints","description":"Enforces hard limits on CPU cores, memory allocation, and execution time for each code execution to prevent resource exhaustion and runaway processes. Automatically terminates executions that exceed limits and returns error status, protecting the host infrastructure and ensuring fair resource allocation across concurrent sandboxes.","intents":["Prevent infinite loops or memory leaks from crashing the execution environment","Enforce fair resource sharing when multiple AI agents execute code concurrently","Detect and reject computationally expensive code before it consumes excessive resources","Guarantee execution latency SLAs by enforcing timeout limits"],"best_for":["Multi-tenant platforms running untrusted code from multiple users","AI agent systems that need predictable resource consumption","Educational platforms teaching programming without risking infrastructure stability"],"limitations":["Resource limits may be too restrictive for legitimate long-running workloads (e.g., large data processing)","Timeout errors don't distinguish between slow code and infinite loops — both fail identically","Memory limits are per-process, not per-sandbox — multiple processes can collectively exceed intended limits","CPU throttling may cause unpredictable performance degradation rather than hard failures"],"requires":["E2B API key","Understanding of resource requirements for target code","Error handling for timeout/resource limit exceptions"],"input_types":["code with unknown resource requirements","user-submitted code from untrusted sources"],"output_types":["execution results (if completed within limits)","timeout/resource limit error messages","partial output (if available before termination)"],"categories":["safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-e2b__cap_5","uri":"capability://tool.use.integration.streaming.output.capture.with.real.time.stdout.stderr.access","name":"streaming output capture with real-time stdout/stderr access","description":"Captures stdout and stderr from executing code in real-time and streams results back to the client as they are produced, rather than buffering until completion. Allows AI agents and developers to monitor long-running executions and react to intermediate output without waiting for the full execution to finish.","intents":["Monitor progress of long-running data processing or ML training scripts","Stream logs from code execution to user interfaces in real-time","Implement interactive debugging where agents can see output and adjust execution mid-stream","Build responsive AI agents that don't block on code execution completion"],"best_for":["Interactive development tools and REPLs","Long-running batch processing workflows","AI agents that need to monitor and react to execution progress"],"limitations":["Streaming adds complexity to client implementations — requires handling partial results and stream termination","Large output volumes (megabytes of logs) may overwhelm clients or network bandwidth","Streaming latency depends on network conditions — not suitable for ultra-low-latency use cases","MCP protocol may not support true streaming — may require polling or WebSocket fallback"],"requires":["E2B API key","Client capable of handling streaming responses (WebSocket or Server-Sent Events)","Code that produces stdout/stderr output"],"input_types":["code that prints to stdout/stderr"],"output_types":["streamed stdout/stderr chunks","final exit code and summary"],"categories":["tool-use-integration"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-e2b__cap_6","uri":"capability://safety.moderation.environment.variable.and.secret.injection.with.secure.handling","name":"environment variable and secret injection with secure handling","description":"Allows passing environment variables and secrets (API keys, database credentials) to sandboxed code execution without embedding them in code or logs. Implements secure injection mechanisms that prevent accidental exposure of secrets in stdout/stderr or error messages.","intents":["Pass API keys to code without hardcoding them in scripts","Inject database credentials for code that needs to connect to external services","Manage environment-specific configuration (dev vs. prod) without code changes","Prevent secrets from leaking into execution logs or error messages"],"best_for":["Production code execution pipelines that interact with external services","Multi-environment deployments (dev, staging, prod) with different credentials","Security-conscious teams that need audit trails for secret access"],"limitations":["Secrets are still accessible to code once injected — no protection against malicious code reading environment variables","No built-in secret rotation — requires external secret management system for key rotation","Environment variables are visible to all processes in the sandbox — no per-process isolation","Audit logging of secret access may not be available depending on E2B plan"],"requires":["E2B API key","Secrets/credentials to inject (API keys, database URLs, etc.)","Code that reads from environment variables (os.environ, process.env, etc.)"],"input_types":["environment variable key-value pairs","secret strings"],"output_types":["code execution results (with secrets redacted from logs)"],"categories":["safety-moderation"],"confidence":0.5,"matches":0,"success_rate":0},{"id":"awesome-e2b__cap_7","uri":"capability://data.processing.analysis.artifact.download.and.export.with.file.retrieval.api","name":"artifact download and export with file retrieval api","description":"Provides API endpoints to download files generated within the sandbox after code execution completes. Supports downloading individual files or entire directory trees as archives (tar.gz, zip), with optional compression and size limits to prevent abuse.","intents":["Retrieve generated reports, datasets, or images from code execution","Export results from data processing pipelines for downstream analysis","Build file-based workflows where code generates artifacts consumed by other systems","Download execution logs and debug information for post-mortem analysis"],"best_for":["Data processing and ETL workflows that generate output files","AI agents that create artifacts (images, documents, code) as part of execution","Batch processing systems that need to retrieve results asynchronously"],"limitations":["Download latency depends on file size and network bandwidth — large files may take minutes to retrieve","Files must be explicitly downloaded before sandbox cleanup — no automatic persistence","Archive creation (tar.gz, zip) adds CPU overhead and latency for large directory trees","No built-in versioning or retention — old artifacts are lost when sandbox terminates"],"requires":["E2B API key","Sandbox session ID or execution ID","File paths relative to sandbox root"],"input_types":["file paths (relative or absolute)","directory paths for bulk export"],"output_types":["file content (binary or text)","archive files (tar.gz, zip)","file metadata (size, modification time)"],"categories":["data-processing-analysis"],"confidence":0.5,"matches":0,"success_rate":0}],"trust":{"score":26,"verified":false,"data_access_risk":"high","permissions":["E2B API key (free tier available)","MCP-compatible client (Claude Desktop, custom MCP host, etc.)","Network connectivity to E2B's hosted infrastructure","E2B MCP server running (provided as open-source package)","E2B API key for authentication","E2B API key","Knowledge of target language syntax and standard library","Network connectivity for package downloads (pip, npm, etc.)","Code that explicitly writes to /tmp or home directory","Mechanism to download files before sandbox cleanup (API call or explicit export)"],"failure_modes":["Network isolation may block external API calls unless explicitly configured","Ephemeral sandboxes don't persist state between executions — requires explicit file/database writes","Cold start latency (~1-3 seconds) for new sandbox instances","Resource limits (CPU, memory, disk) may constrain long-running or memory-intensive workloads","No direct access to local file system — requires explicit file upload/download via API","MCP protocol overhead adds ~50-100ms per tool invocation","Tool schema validation may reject complex or dynamic input structures","Limited to MCP-compatible clients — no direct REST API exposure","Requires MCP server setup and configuration (though E2B provides pre-built server)","Language runtimes share the same sandbox — no isolation between Python and Node.js processes","builder identity is not verified yet","no observed match outcomes yet"],"rank_breakdown":{"adoption":0.05,"quality":0.26,"ecosystem":0.39999999999999997,"match_graph":0.25,"freshness":0.52,"weights":{"adoption":0.25,"quality":0.25,"ecosystem":0.15,"match_graph":0.23,"freshness":0.12}},"observed_outcomes":{"matches":0,"success_rate":0,"avg_confidence":0,"top_intents":[],"last_matched_at":null},"maintenance":{"status":"active","updated_at":"2026-06-17T09:51:03.038Z","last_scraped_at":"2026-05-03T14:00:15.503Z","last_commit":null},"community":{"stars":null,"forks":null,"weekly_downloads":null,"model_downloads":null,"model_likes":null}},"distribution":{"claim_url":"https://unfragile.ai/submit?claim=e2b","compare_url":"https://unfragile.ai/compare?artifact=e2b"}},"signature":"OTDLb4VVb0LHVBYeAnwT0M6D8GMHhcYeRoK6c0m23m4PJe7lMrRIegHhxDLYkCeKYqN4bymBJEhe3jQn/21GBg==","signedAt":"2026-06-20T03:44:39.654Z","signedBy":"unfragile.ai","version":1},"_links":{"self":"https://unfragile.ai/api/v1/passport/e2b","artifact":"https://unfragile.ai/e2b","verify":"https://unfragile.ai/api/v1/verify?slug=e2b","publicKey":"https://unfragile.ai/api/v1/trust-passport-public-key","spec":"https://unfragile.ai/trust","schema":"https://unfragile.ai/schema.json","docs":"https://unfragile.ai/docs"}}