{"id":"kraklabs-cie","name":"cie","homepage":"https://kraklabs.com/cie","repo_url":"https://github.com/kraklabs/cie","category":"devtools","subcategories":[],"tags":["mcp","code-intelligence","semantic-search","call-graph","tree-sitter","local-indexing","devtools","go"],"what_it_does":"CIE (Code Intelligence Engine) is a local CLI that indexes a codebase and exposes semantic code search, call-graph/path analysis, and code/HTTP endpoint discovery to AI agents via the Model Context Protocol (MCP). It stores an embedded CozoDB/RocksDB index locally and can optionally use local or hosted embedding/LLM providers for semantic search and narrative analysis.","use_cases":["Semantic search for functions/types by intent (e.g., “where is auth middleware” )","Tracing call graphs and execution paths to understand how a function is reached","Discovering HTTP/REST endpoints (Go framework conventions) and gRPC services (from .proto)","Providing agents with structured code intelligence to reduce tool round-trips","Auditing/verification tasks via pattern absence checks (cie_verify_absence)"],"not_for":["A hosted SaaS for running on remote code (it is positioned as local-only)","High-availability production APIs for end-user traffic (it’s primarily a local indexing/querying tool)","Security/compliance systems that require formally documented threat models and guarantees beyond local storage claims"],"best_when":"You want an offline/local code-knowledge layer for an AI coding agent, especially when you need call graphs and structured code search across a large repository.","avoid_when":"You need strict RBAC/authN/authZ guarantees for multi-tenant remote access, or you require guaranteed semantic results without any embedding model/providers.","alternatives":["Sourcegraph/Code Search products","OpenRewrite/ctags-based static analysis plus language-specific tooling","RAG over code using embeddings + vector DB (with custom ingestion pipelines)","Other local code intelligence tools (e.g., ripgrep + tree-sitter based indexers)","CodeQL-style approaches (where supported)"],"af_score":60.2,"security_score":35.0,"reliability_score":22.5,"package_type":"mcp_server","discovery_source":["github"],"priority":"high","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-03-30T15:39:14.838599+00:00","interface":{"has_rest_api":false,"has_graphql":false,"has_grpc":false,"has_mcp_server":true,"mcp_server_url":null,"has_sdk":false,"sdk_languages":[],"openapi_spec_url":null,"webhooks":false},"auth":{"methods":["Local/offline mode (no auth described for the MCP server)","Embedding provider authentication via environment variables (e.g., OpenAI API key)"],"oauth":false,"scopes":false,"notes":"No auth mechanism for the MCP server is described in the provided README; access is implied to be local-process based. For embedding/LLM features, credentials are configured via env vars in YAML (e.g., OpenAI API key / Ollama base_url)."},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":["CIE Enterprise (commercial)"],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"Open source (AGPL v3) is available via releases/binaries. Enterprise is offered commercially, but no pricing details are included in the provided content."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":["Local filesystem only (embedded index in ~/.cie/data/<project> by default)"],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":60.2,"security_score":35.0,"reliability_score":22.5,"mcp_server_quality":80.0,"documentation_accuracy":75.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":90.0,"rate_limit_clarity":0.0,"tls_enforcement":20.0,"auth_strength":30.0,"scope_granularity":20.0,"dependency_hygiene":50.0,"secret_handling":60.0,"security_notes":"Security posture is positioned as local-only data storage (code never leaves the machine) and embedded DB use. However, the provided content does not document MCP transport security/auth controls, threat model, or rate limiting. Secrets for embedding/LLM providers are configured via YAML/env vars; guidance on preventing logging/accidental exposure is not provided in the README. TLS cannot be meaningfully assessed for the MCP server because no network/auth details are described.","uptime_documented":0.0,"version_stability":40.0,"breaking_changes_history":20.0,"error_recovery":30.0,"idempotency_support":"false","idempotency_notes":"Indexing/re-indexing commands are described, but idempotency semantics for MCP tools (safe retries) are not documented in the provided README.","pagination_style":"none","retry_guidance_documented":false,"known_agent_gotchas":["Semantic search may require embeddings; without configuring an embedding provider (e.g., Ollama/OpenAI/Nomic) the semantic tool’s results may be unavailable or degraded while structural tools still work.","Because the index is local, agents need to ensure the correct project_id and that indexing has been run before querying.","No documented auth/rate-limit/error-contract details for the MCP server in the provided README; agents should be prepared for tool failures without standardized guidance."]}}