{"$schema":"https://wellknown.network/schemas/agent-record-v1.json","schemaVersion":"1","id":"ag_n59s4c3gmy86","handle":"sablier-mcp","url":"https://wellknown.network/agents/sablier-mcp","links":{"self":"https://wellknown.network/agents/sablier-mcp/record.json","html":"https://wellknown.network/agents/sablier-mcp","markdown":"https://wellknown.network/agents/sablier-mcp/record.md","api":"https://wellknown.network/api/v1/agents/sablier-mcp","status":"https://wellknown.network/api/v1/agents/sablier-mcp/status","claim":"https://wellknown.network/agents/sablier-mcp/claim","claimApi":"https://wellknown.network/api/v1/claims","claimDescriptor":"https://wellknown.network/agents/sablier-mcp/claim.json","badge":"https://wellknown.network/agents/sablier-mcp/badge.svg","openapi":"https://wellknown.network/openapi.json","history":"https://wellknown.network/api/v1/agents/sablier-mcp/history","tools":"https://wellknown.network/api/v1/agents/sablier-mcp/tools"},"ard":{"identifier":"urn:air::server:sablier-mcp","type":"application/mcp-server-card+json"},"kind":"mcp_server","declared":{"name":"sablier-mcp","summary":"Sablier MCP — plug Wall Street-grade portfolio analytics, stress-testing, and SEC filing intelligence into any AI assistant. What takes quants & analysts weeks, done in 2 minutes.","description":"# Sablier MCP Server\n\n[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](LICENSE)\n[![Python 3.11+](https://img.shields.io/badge/python-3.11+-blue.svg)](https://www.python.org)\n[![MCP 1.26+](https://img.shields.io/badge/MCP-1.26+-green.svg)](https://modelcontextprotocol.io)\n\nAn [MCP (Model Context Protocol)](https://modelcontextprotocol.io) server that lets AI assistants analyze portfolios, stress-test scenarios, generate synthetic market paths, and scan SEC filings — in under 2 minutes.\n\n## What This Does\n\nConnect Sablier to Claude, ChatGPT, or any MCP-compatible AI assistant. The agent gets ~70 tools to:\n\n**Scan SEC filings & earnings calls** — AI reads every company's 10-K, 10-Q filings and earnings call transcripts, then scores how exposed each holding is to any theme you ask about (0-100 scale with evidence). _\"How exposed is my portfolio to China supply chain risk?\"_ — scored, evidenced, and ranked in seconds.\n\n**Compute factor exposures** — Measures how each stock responds to market drivers (interest rates, VIX, dollar index, oil, credit spreads, etc.). Factor betas are estimated on a rolling window of recent data so they reflect current market conditions. Supports both linear and nonlinear (GAM) factor models.\n\n**Stress-test with scenarios** — _\"What if VIX hits 40?\"_ or _\"What if the Fed raises rates to 6%?\"_ Run Monte Carlo simulations to get per-asset expected returns, Value-at-Risk, Expected Shortfall, and full return distributions.\n\n**Generate synthetic market paths** — Train a generative flow model on the joint distribution of assets and factors. Generate hundreds of realistic future trajectories, optionally constrained (_\"paths where gold stays above $3000\"_). Forward-test strategies across many scenarios.\n\n**Real-time market intelligence** — Get a Bloomberg-terminal-grade briefing with 50+ indicators, z-scores, regime signals, and cross-asset analysis in one call.\n\n**Manage portfolios** — Create and track portfolios with live pric…","publisher":null,"homepage":"https://sablier.ai","repository":"https://github.com/sablier-it/sablier-mcp/issues","version":"0.13.2","license":"MIT","protocols":["mcp"],"tags":["ai","sec","factor-model","finance","mcp","portfolio","risk","stress-testing"],"pricing":null,"endpoints":[{"url":"pypi:sablier-mcp","type":"package_pypi","auth":null,"probeable":false}],"skills":null,"tools":null,"extra":null,"attribution":{"kind":"pypi","name":"pypi","license":"pypi","repoUrl":"pypi","summary":"pypi","version":"pypi","description":"pypi","homepageUrl":"pypi"}},"derived":{"capabilities":[{"slug":"code.testing","name":"Testing","confidence":1,"provenance":"derived"},{"slug":"finance.markets","name":"Markets & Trading","confidence":1,"provenance":"declared"}],"categories":["code","finance"],"language":"en"},"observed":{"status":"unknown","statusReason":"Distributed as a package to run locally; no network endpoint to check.","lastOkAt":null,"lastProbedAt":null,"statusComputedAt":null,"reliability30d":null,"latestObservations":[],"tools":null,"package":{"name":"sablier-mcp","registry":"pypi","observedAt":"2026-11-04T00:27:11.926Z","publishedAt":"2026-05-19T10:00:47.644673Z","latestVersion":"0.13.2"},"toolSurface":null,"endpointFacts":[]},"verification":{"claimed":false,"claimedAt":null,"proofs":[]},"provenance":{"sources":[{"source":"pypi","key":"sablier-mcp","url":"https://pypi.org/project/sablier-mcp/","firstSeenAt":"2026-09-10T11:27:39.954Z","fetchedAt":"2026-11-04T00:25:02.850Z","normalizedAt":"2026-11-04T00:25:02.850Z"}]},"firstSeenAt":"2026-09-10T11:27:39.954Z","updatedAt":"2026-11-04T00:27:11.926Z"}