Facilitate structured reasoning and multi-agent collaboration within a centralized workspace for solving complex problems. Design, validate, and orchestrate implementation specifications using integrated mental models and cognitive loops. Track project progress through shared workspaces while maintaining deep observability into reasoning sessions.
Stack Exchange is a network of Q&A communities where users ask questions, share knowledge, and collaborate on topics like coding, math, and more
Thriya is a judgment and operating-memory layer for AI-native work. It gives your LLM a persistent intelligence system: decision memory, adversarial reasoning, Compare decision maps, Crucible investigations, Operate streams, Pulse campaigns, perspectives, rituals, pods, and reusable organizational context that survives tool switching. What you can do with Thriya via MCP: Think with memory Ask Quick Think questions grounded in your saved perspectives, decision history, workspaces, and Operate streams. Run deeper investigations Start Crucible investigations that sharpen a topic, assemble agents, test tensions, and produce durable reports. Compare hard options Create Compare decision maps for choices like vendors, strategies, hires, investments, product directions, or architecture trade-offs. Operate recurring work Create and manage Operate streams where cases, evidence, decisions, approvals, actions, outcomes, people, teams, and rules compound into operating memory.
Anti-firehose options-flow intelligence for AI agents. Every night the engine scans the US options market for unusual activity and curates hard - down to a small, high-signal candidate pool with point-in-time features, realized MFE/MAE opportunity surfaces, outcome labels, and methodology playbooks. Deliberately no "pick" endpoint: your agent reasons over data primitives to its own contract and exit. Free anon tier works with no account (daily report, playbooks, explainers). Pro tools require Agent Access ($39/mo) via a Bearer API key.
The Nimble MCP Server gives AI agents the ability to search, extract, map, crawl, and structure data from any website in real time. It exposes Nimble’s full web data platform as MCP tools that any compatible AI client can use.
Make structured decisions in under 100ms — faster than any LLM API call. Define any decision type your app needs, train a lightweight ML model from AI-generated examples, and get instant decisions with confidence scores and reason codes. No ML team or historical data required. From moderation to routing to fraud — if an LLM can judge it, Sparkient can compile it.
Map text into knowledge graphs to create a structured representation of conceptual relations and topical clusters in your documents. Detect content gaps between the topical clusters and generate research questions to drive research and content creation using the powerful Graph RAG technology underpinning InfraNodus. Get additional insights about texts: main topics, keywords, and underlying themes. Connect to your existing InfraNodus graphs or create new ones to enrich analysis and outputs.
Location and routing intelligence for AI agents — geocoding, turn-by-turn truck routing with hazmat & dimension constraints, live traffic, 16-day weather forecasts, drive-time isochrones, and place search. Planet-wide coverage.
Verifiable document intelligence for AI agents. Extract text, tables, and structured data from PDFs and URLs. Summarize, answer questions, check claims, and translate — all with cited evidence. Store tamper-evident evidence bundles with cryptographic signatures and on-chain attestation via Base L2. Cross-document semantic search and Q&A across named collections. Pay per call with USDC (x402) or use an API key.
Financial reasoning infrastructure for AI agents - typed models, deterministic compilation, cryptographic receipts via MCP
Create and edit diagrams, wireframes, and sketches on a shared canvas. Export drawings and collaborate visually in real time.
Official Nordic and EU business data for AI agents — 15 countries, 11 tools. Look up companies, validate VAT, run KYB reports, screen sanctions, autocomplete addresses, resolve LEI, plus runtime discovery of 230+ endpoints. Backed by official registries (CVR, Brønnøysund, Bolagsverket, Companies House, VIES, OFAC, GLEIF, OpenSanctions).
OrgX is coordination infrastructure for AI-native teams. It gives your LLM a persistent organizational layer: initiatives with milestones and tasks, human-in-the-loop decision workflows, specialist agent delegation, and cross-session memory that survives tool switching. What you can do with OrgX via MCP: Scaffold initiatives — decompose a goal into workstreams, milestones, and tasks in one call Manage decisions — create, review, approve, or reject decisions with audit trails Delegate to specialist agents — spawn tasks for domain agents (engineering, marketing, product, sales, operations, design) and monitor their progress Query organizational memory — search past decisions, artifacts, and learnings across initiatives Track progress — get initiative health, agent status, blockers, and morning briefs Plan and prioritize — score queues, get next-action recommendations, and run autonomous sessions with budget guardrails OrgX is built for solo founders and small teams who work across mult
The intelligence layer agents use before they act, sourced answers on the agent economy. Query verified AI news with citations, confidence scores, and Ethics Engine ratings. Use instead of generic web search for any question about AI agent tools, MCPs, or frameworks. Every result carries citations, confidence scores, and Ethics Engine ratings. Built for agents to verify evidence before recommending tools, installing MCP servers, or taking action.
Agent Personas for Claude. 14 MCP tools, 8 built-in personas (CEO, CFO, CMO, CTO, PM, Analyst, Support, Creative), custom personas, chained workflows. Zero extra API cost. Free tier.
Diagnoses, drugs & lab codes: ICD-11, SNOMED, LOINC, RxNorm, MeSH, ATC, CID-10. 37 tools, MIT.
Access structured interview notes and candidate insights. Search past interviews, review feedback, and track hiring decisions.
AI reasoning checks any document for internal consistency and completeness against the applicable international standard for its type, before your agent acts on it.
VAST XML validation MCP server for programmatic video advertising. Over $30 billion in annual CTV and video ad spend flows through VAST XML — malformed tags cause lost impressions, broken tracking, and revenue discrepancies between platforms. Validates VAST tags against IAB Tech Lab VAST 2.0, 3.0, 4.0, 4.1, 4.2, and 4.3 specifications, W3C XML 1.0 well-formedness, RFC 3986 URI syntax, IANA media types, ISO 4217 currency codes, Ad-ID registry format, and IAB SIMID 1.0–1.2. 118 rules covering required fields, schema validation, structural correctness, security, deprecated features, and value formats. Tools: validatevast (validate inline XML), validatevasturl (fetch and validate a VAST URL, following wrapper chains), listrules (browse all 118 rules), explainrule (get fix guidance for a specific rule), fixvast (auto-fix common issues). Built on a zero-dependency Rust core. Sub-millisecond latency. No data retention — VAST XML is validated ephemerally and never stored. Self-hostabl
datamcp is a hosted MCP gateway for PostgreSQL 12+, MySQL, and OpenAPI 3.x. Connect a database or API once, create scoped MCP links for Cursor, Claude, ChatGPT, VS Code, and other compatible clients, and keep source credentials server-side. Control accessible tables, operations, API endpoints, and HTTP methods per link. MCP clients authenticate with an API key or OAuth 2.0 with PKCE. PostgreSQL and MySQL query activity is available in the dashboard. Free tier available; no self-hosting.
Clean US equity total returns + institutional risk decomposition, via MCP. RiskModels gives agents dividend-adjusted total return series for any US stock or ETF — and decomposes both the return and its risk into market → sector → subsector → residual layers, with executable ETF hedge ratios for each. Built on ERM3, a hierarchical factor model with orthogonalized factor construction over ~3,000 US equities (16k-name historical panel), daily history back to 2006. One MCP call covers performance tracking, return attribution, manager-skill / 13F review, hedging, stat-arb, or feeding clean returns into your own models. Capabilities Returns — daily dividend-adjusted total (gross) return series, point-in-time / time-safe Return attribution — gross return split into L1/L2/L3 factor vs residual; isolates the residual (stock-picking / alpha) series Risk decomposition — additive market / sector / subsector / residual variance shares (su
