{"id":"pathintegral-institute-mcp-science","name":"mcp.science","homepage":"https://mcp.science/","repo_url":"https://github.com/pathintegral-institute/mcp.science","category":"ai-ml","subcategories":[],"tags":["mcp","ai-agents","science","tooling","research"],"what_it_does":"mcp.science is an MCP server package intended to expose “science” related tools/data to an AI agent via the Model Context Protocol (MCP). Specific tool capabilities, endpoints, and behavior are not provided in the prompt content, so the evaluation is based only on the package name/declared MCP nature.","use_cases":["Agent-assisted scientific research workflows (summarization, querying, or retrieval) via MCP tools","Integrating science datasets/tools into an agent conversation context","Building agent systems that require a standardized MCP interface for external capabilities"],"not_for":["Production systems that require a fully specified, guaranteed tool contract without verifying the actual MCP server implementation","Environments that disallow third-party network access or external retrieval without strict controls","Use cases requiring REST/GraphQL/SDK interfaces rather than MCP"],"best_when":"When you want standardized tool access from an LLM agent using MCP, and you will validate the actual exposed tools/parameters in the repository.","avoid_when":"When you need strict guarantees about authentication, rate limits, error formats, idempotency, or pagination—none of these are verifiable from the provided information.","alternatives":["Other MCP servers with documented tool contracts (e.g., browser/search/retrieval-focused MCP servers)","Direct use of science APIs via REST with OpenAPI and SDKs","Frameworks such as LangChain/LlamaIndex with dedicated retrievers/datasets (non-MCP)"],"af_score":34.0,"security_score":39.5,"reliability_score":7.5,"package_type":"mcp_server","discovery_source":["github"],"priority":"high","status":"evaluated","version_evaluated":null,"last_evaluated":"2026-03-30T13:44:24.177066+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":[],"oauth":false,"scopes":false,"notes":"No authentication mechanism details were provided in the prompt content for this package."},"pricing":{"model":null,"free_tier_exists":false,"free_tier_limits":null,"paid_tiers":[],"requires_credit_card":false,"estimated_workload_costs":null,"notes":"Pricing information was not provided."},"requirements":{"requires_signup":false,"requires_credit_card":false,"domain_verification":false,"data_residency":[],"compliance":[],"min_contract":null},"agent_readiness":{"af_score":34.0,"security_score":39.5,"reliability_score":7.5,"mcp_server_quality":40.0,"documentation_accuracy":30.0,"error_message_quality":0.0,"error_message_notes":null,"auth_complexity":60.0,"rate_limit_clarity":10.0,"tls_enforcement":60.0,"auth_strength":30.0,"scope_granularity":20.0,"dependency_hygiene":40.0,"secret_handling":50.0,"security_notes":"No repository/implementation details were provided. As a result, TLS/auth/secret handling are assessed conservatively based on typical MCP deployments, not confirmed facts. Validate transport security, credential storage, and logging behavior in the actual code.","uptime_documented":0.0,"version_stability":0.0,"breaking_changes_history":0.0,"error_recovery":30.0,"idempotency_support":"false","idempotency_notes":null,"pagination_style":"none","retry_guidance_documented":false,"known_agent_gotchas":["Because tool contracts aren’t provided here, the agent may need to be resilient to unexpected tool names/parameters and to validate returned data formats.","Scientific retrieval workflows can be sensitive to query formulation; without documented guidance, agents may produce inconsistent queries."]}}