PathFi runs the real numbers on any decision — one you're about to make, are rethinking, or already made — and keeps score on how its odds hold up against what actually happens. Decision-grade math for career, money, business, and prediction-market calls: thousands of simulated outcomes, calibrated against reality, not just a confident guess.
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For AI agents — MCPBundles Directory API
Recommended: Directory API v1 over HTTP for detail and anonymous invoke when eligible (not MCP JSON-RPC on the publisher URL; no user MCPBundles credentials on v1).
GET https://www.mcpbundles.com/api/directory/v1/servers/pathfi-mcp-ba8838d2d1
GET https://www.mcpbundles.com/api/directory/v1/servers/pathfi-mcp-ba8838d2d1?live=1 (optional live refresh)
GET https://www.mcpbundles.com/api/directory/v1/servers/pathfi-mcp-ba8838d2d1/tools/<tool> (one tool: schema + invoke.url)
POST https://www.mcpbundles.com/api/directory/v1/servers/pathfi-mcp-ba8838d2d1/tools/{tool}
POST body: flat JSON of tool argument names and values; not an arguments wrapper. Replace {tool} with a tool name from GET detail.
Restricted agent shell (ChatGPT Codex desktop, some IDE sandboxes):
Default command sandboxes often block outbound network. curl exit 6 or "Could not resolve host" for www.mcpbundles.com is usually sandbox DNS — not evidence this site is down.
Retry the same Directory API GET with sandbox_permissions "require_escalated" and a one-sentence justification on the shell tool (Codex on-request approval). Do not tell the user the site is unreachable from sandbox curl alone.
Example justification: Run the public MCPBundles Directory API search outside the command sandbox to complete the user's MCP server lookup.
If the agent has browser access (e.g. Codex @Browser): open https://www.mcpbundles.com/?q=<query> or stay on this page — no shell network needed. Use WebMCP search_mcp_servers then get_mcp_server (document.modelContext / page tools; refresh with fetchTools or getTools if a tool id is missing from the snapshot). Read-only directory search; same index as Directory API v1 GETs. Neither WebMCP nor Directory API v1 uses user MCPBundles credentials.
Without a browser: after escalated curl fails, use GET https://www.mcpbundles.com/?q=<query> with Accept: text/markdown for ranked results.
Hub MCP (connected session): discover_mcp_servers — same filter semantics as search_mcp_servers.
Contract: https://www.mcpbundles.com/agents.md
OpenAPI: https://www.mcpbundles.com/api/directory/v1/openapi.json
Guide: https://www.mcpbundles.com/guides/mcpbundles-directory-api
For MCP client apps (human connect):
MCP connect URL: https://mcp.pathfi.ai/
Skill page: https://www.mcpbundles.com/skills/pathfi-mcp-ba8838d2d1
Explore capabilities (29)
read 5
write 1
other 19
Showing 25 of 29
Showing 25 of 29 tools from the public preview. Connect the server to inspect the full live tool list.
Evaluate16
Get5
Other capabilities4
Get Track Record
read
get_track_record
PathFi's live, publicly checkable forecasting track record: how many forecasts have resolved, the accuracy index (0-100, higher is better), how closely stated chances match what actually happened (versus the market itself), and whether PathFi beats the market's own closing prices. Includes verification links — the methodology page and the pre-registered protocol — so you can check the receipts instead of trusting a claim. Free, no key needed.
Get Track Record — PathFi's live, publicly checkable forecasting track record: how many forecasts have resolved, the accuracy index (0-100, higher is better), how closely stated chances match what actually happened (versus the market itself), and whether PathFi beats the market's own closing prices. Includes verification links — the methodology page and the pre-registered protocol — so you can check the receipts instead of trusting a claim. Free, no key needed.
Get Market Context — Look up a live prediction market (Polymarket URL, Kalshi URL/ticker, or bare slug) and get a decision-ready read: current price, recent movement, how seriously to take the price (heavily traded prices are usually set by informed money; thin markets can be soft), days until resolution, and plain-English guidance on blending your own view with the market. Pure data lookup — fast and free, with generous per-caller limits. No key needed.
Request Calibrated Forecast — Ask PathFi's forecasting engine for a calibrated probability on a live market (Polymarket/Kalshi URL) OR any falsifiable yes/no question with a resolution date. The engine runs live web research, so a run takes 30-90 seconds: this tool returns a jobId immediately — poll get_forecast_result with it for the answer. Requires your pf_ key (the same key proving_ground_register issues) as api_key. Free tier: 5 runs per hour per key with no payment needed; every run does real research. Attach prepaid f
Get Forecast Result — Fetch the result of a request_calibrated_forecast run by jobId. Runs take 30-90 seconds, so poll about every 10 seconds. While the engine is still working you get a status + retry hint; when complete you get a versioned forecast payload (probability, resolution horizon, PathFi's live calibration credentials), the engine's written reasoning, a reasoning-quality check, and any settlement fine-print warnings. Requires the same pf_ key that started the run — results are visible only to the agent tha
Get Balance — Check your prepaid balance for calibrated forecasts. Returns your current balance, how many forecasts that covers, the price per forecast, the minimum top-up, and how to add funds (call create_agent_top_up). Each request_calibrated_forecast run is charged at the price shown; failed runs are refunded minus the compute already spent on your behalf. Requires your pf_ key as api_key.
Get your MCP into directories
A working endpoint is step one. Directory coverage is the coordinated launch across ChatGPT, Claude, Cursor, the MCP Registry, and community indexes.
PathFi runs the real numbers on any decision — one you're about to make, are rethinking, or already made — and keeps score on how its odds hold up against what actually happens. Decision-grade math for career, money, business, and prediction-market calls: thousands of simulated outcomes, calibrated against reality, not just a confident guess.
How do I connect PathFi to my AI agent?
Use the MCP endpoint listed on this page in your MCP client configuration. One-click install pills support Claude, Cursor, VS Code, and other hosts. Copy the remote MCP URL if your client needs a manual entry.
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More in developer tools
Other MCP servers in this category from the directory index
Create Agent Top Up — Add prepaid funds for calibrated forecasts. You pick an amount (in US cents, minimum $25) and this returns a Stripe checkout link. Your human owner opens the link and pays; once the payment clears, your balance updates automatically — poll get_balance to see it. Nothing is charged to you here, and no card details pass through this tool. Requires your pf_ key as api_key.
Evaluate Forecasting Decision — Run structured decision analysis on a binary forecasting question — typically a Polymarket, Kalshi, or other prediction-market question, but also applicable to any "is this likely or not?" question with a stated market consensus or third-party probability. Returns a combined posterior probability (blending the user's view with the market's view via Bayesian update), an estimated stake size with cautious/aggressive variants, and edge-sensitivity bands. Use this when the user is comparing their vi
Evaluate Real Estate Decision — Evaluate the financial trade-off between buying and renting a home over a user-specified time horizon. Returns the break-even number of years until buying overtakes renting+investing-the-difference, the net financial advantage at the user's stated horizon, and sensitivity bands across appreciation rate, investment return, rent growth, and horizon. Use this when the user is comparing a specific home price to a specific monthly rent and wants to know which is the better long-term financial decisio
Evaluate Big Purchase Decision — Compare 2-4 big-purchase alternatives by total cost of ownership over their expected useful life. Returns the cheapest alternative by present-value cost, the dollar gap to the runner-up, whether the ranking is stable under realistic perturbations, and what parameter the answer is most sensitive to. Use this for: car comparisons (gas vs EV, new vs used), appliance buy-vs-repair decisions, expensive electronics, solar/heat-pump installations, or any consumer-durable decision where the user wants t
Evaluate Career Dcf Decision — Evaluate a career change (stay vs new offer) by computing present-value of each path's compensation over a stated horizon, plus optionality value of preserving switching flexibility, minus one-time switching costs. Returns: decision verdict + dollar advantage + sensitivity bands + ranking stability. Use this when the user is comparing their current job against a specific new offer. Requires: current path (base + bonus % + raise rate + RSU stream) + offer path (base + bonus % + raise rate + signi
Evaluate Negotiation Decision — Recommend an optimal salary counter-offer that maximizes expected value, given the company's initial offer, your best-alternative-to-negotiated-agreement (BATNA), and your sense of the company's flexibility (low / medium / high). Uses a logistic acceptance-probability model: low flexibility means the company accepts within ~10% of their initial; high flexibility means up to ~30%. Returns: recommended counter + expected value + acceptance probability + 4 strategy variants (safe / moderate / aggre
Evaluate Debt Vs Invest Decision — Compare paying down debt vs investing an equal monthly amount over a horizon. Returns: recommended path + dollar advantage + per-path net worth at horizon. Adjusts for mortgage-interest-deductibility (if flagged) and capital-gains tax on the invest path. Use this for common consumer questions like "should I prepay my 5% mortgage or put the money in S&P?" or "extra paycheck — pay down student loans or invest?". Requires: debt_balance, debt_rate, monthly_extra, horizon_years; optional marginal_tax
Evaluate Education Decision — Evaluate whether a degree, certification, or training program will pay back over the user's post-graduation career. Computes net present value: post-grad salary premium summed across career years, minus tuition + foregone earnings during the program. Returns: recommendation (pursue / skip / roughly-even) + NPV + payback years. Use for: MBA, master's degree, coding bootcamp, certifications. Requires: tuition_cost, in_school_annual_salary (0 if you quit), no_degree_annual_salary (baseline if you d
Evaluate Geographic Relocation Decision — Compare two locations (current vs new) on purchasing-power basis adjusted for cost-of-living differential, tax differential, and one-time moving costs. Returns: move / stay / roughly-even recommendation + dollar advantage + per-location purchasing power. Use for: city-to-city moves, state-to-state moves, country moves (with COL index in same currency). Requires: current + new (each with name + annual_salary + col_index) + horizon_years; optional effective_tax_rate per location (default 28%), mov
Evaluate Insurance Decision — Evaluate whether to buy a specific insurance policy (auto, renters, umbrella, extended warranty, etc.). Computes expected payout vs premium plus a risk-aversion adjustment for losses that would exceed liquid savings. Returns: buy / skip / roughly-even + dollar value per year. Use when comparing a specific policy against going self-insured. Requires: annual_premium, annual_loss_probability (decimal — e.g., 0.05 for "5% chance per year"), loss_magnitude, coverage; optional deductible, liquid_savin
Evaluate Health Qaly Decision — CRITICAL — DECISION SUPPORT ONLY, NOT MEDICAL ADVICE. Compares two health paths (treat vs decline) on quality-adjusted life-years (QALY) basis. Returns a math-favored direction + net QALYs + dollar-value-equivalent. Use as a thinking aid when discussing a specific treatment with the user's doctor — NEVER as a substitute for medical advice. Requires: years_remaining, quality_with_treatment (0-1), quality_without_treatment (0-1), treatment_cost; optional life_years_extension (years added by treatm
Evaluate Pricing Decision — Find the price that maximizes profit (or revenue if no marginal cost) using a constant-elasticity demand model. Returns: recommended price + expected demand + baseline-vs-recommended profit + per-price-point breakdown + a scan-boundary flag. Requires: baseline_price, baseline_demand, price_elasticity (NEGATIVE number per economics convention — typical −0.5 to −3). Optional: marginal_cost (for profit max), fixed_cost (display only). NOT pricing or business advice. Constant-elasticity is an approx
Evaluate Ab Test Design — Compute required sample size for an A/B test to detect a minimum lift at given significance + power. Returns: sample size per arm + total + days-to-significance (if daily_traffic_per_arm given). Uses two-proportion z-test, two-sided. Requires: baseline_conversion (decimal), min_detectable_lift (decimal, absolute pp). Optional: alpha (default 0.05), power (default 0.80), daily_traffic_per_arm. IMPORTANT: this is fixed-horizon design — sequential / always-valid testing needs separate correction (m
Evaluate Product Launch Bass — Forecast new-product adoption using the Bass (1969) diffusion model. Returns: peak adoption period + peak adopters + cumulative at horizon + market capture fraction + per-period adoption curve. Requires: market_size (total eventual adopters), forecast_periods. Optional: p (innovation coefficient, default 0.01), q (imitation, default 0.40). Typical ranges from published Bass studies: p 0.001-0.03, q 0.3-0.5. For specific industries (smartphones, EVs, streaming services), there's published meta-an
Evaluate Investment Kelly — Kelly criterion position sizing for a binary investment decision (concentrated equity, asymmetric-payoff trade, options with known max-loss). Returns a quarter-Kelly suggestion with a 25% humility cap, plus full/half Kelly as reference. Requires: win_probability (0.01-0.99), win_multiplier (e.g., 2 for double), bankroll. Optional: loss_multiplier (default 1 = lose entire stake). NOT investment advice. PathFi is not a registered investment adviser. The accuracy of Kelly sizing depends ENTIRELY on
Evaluate Hire Vs Skip — Expected-value math for an INDIVIDUAL final-round hire decision. Returns net expected value over horizon + math-favored direction (hire / skip / roughly-even), factoring productivity ramp + turnover risk + expected wrong-hire cost. Requires: expected_annual_value (productivity contribution at full ramp), fully_loaded_cost, ramp_months, retention_probability, horizon_years. Optional wrong_hire_cost (default 1.5× fully-loaded cost). CRITICAL: do NOT use this for screening candidates or filtering a
Evaluate Fundraising Decision — Compare two fundraising scenarios (e.g., $2M @ $10M post-money vs $5M @ $20M post-money) and returns the one with higher expected founder-retained exit value, factoring dilution + runway + exit probability. Requires: current_founder_ownership, monthly_burn, months_to_exit, exit_probability, expected_exit_valuation, scenarios (exactly 2 with name + raise_amount + post_money_valuation; optional option_pool_expansion). NOT investment, legal, or securities advice. PathFi is not a registered investme
Get Calibration Record — Look up a PathFi user's public track record by username. Returns their accuracy rate, total and resolved call counts, current streak, accuracy by category, and their most recent public forecasts. Only forecasts the user chose to make public are included. Use this to check how well a forecaster has actually performed before weighing their opinion.
Verify Forecast Outcome — Check whether a specific PathFi forecast has resolved, and how it turned out. Given a forecast ID (the id in a pathfi.ai/f/{id} link), returns the recorded outcome — what actually happened, when it resolved, and the accuracy scores — or a pending status if the question has not settled yet. Only forecasts the owner has shared (a live pathfi.ai/f/{id} link) can be verified; private or removed forecasts return not_available.
Lookup Market — Resolve a Polymarket URL (or bare market slug) to live market metadata: title, current prices, volume, end date, and resolution details. Use this to fetch the market consensus before evaluating a forecasting decision or recording a call.
Showing the first 25 tools — full list and schemas: Directory API.
How many tools does PathFi provide?
MCPBundles probed 29 tools on the live server. The tool list on this page reflects what was discovered at the last refresh — connect your client to see the full set available to your session.
What authentication does PathFi require?
No provider sign-in was required during MCPBundles' probe. Your client may still need MCPBundles credentials depending on how you connect.
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