User Comments

Nixc0rdant, which programming language are you using for your Betfair projects?

While different languages might be used, I find that statically typed programming languages like F# and .NET languages such as C# or Visual Basic do not require loading an entire source code codebase.

For instance, with F#, we have MCP servers that can explore any type of referenced library. This approach prevents hallucination and avoids having to process millions of tokens just to browse the entire codebase.

I did not write my own prompts; I had the LLM generate them, which you can see in experiments on my GitHub.

I use DeepSeek models, which offer a 1M context window, enough for an entire session within my Betfair strategy project.

In fact, when debugging with an LLM against real-time data, the amount of that data is often larger than my entire strategy project's codebase. After testing over three days, I was genuinely surprised that given all the code DS generated into the output context, it remembered closed market data when asked to calculate P&L from our tests.

These closed markets were not within the bfexplorer application itself; rather, Reasonix/DeepSeek LLM retained this information in its memory context.

My experience is similar to yours. I started before you, and back then there was actually no client app support for connecting to the MCP server because MCP was only a couple of weeks old—it mainly existed in documentation and had initial library implementations for both the server and client. Because of this, I looked for an AI client supporting MCP and found Cherry Studio. I will write some posts about the parts you are interested in, but sometimes it is better to struggle and learn from your mistakes.

I am highly impressed with how you integrated bfexplorer agentic support using the Claude LLM and your strategy execution pipeline that incorporates market data context processing, as any robust strategy must be driven by verifiable data.

Have you also experimented with local LLMs or different AI client applications/harnesses?

A simple test to verify that the bfexplorer MCP is running correctly involves using the 'modelcontextprotocol/inspector.' To do this, run the following command in your terminal:

npx @modelcontextprotocol/inspector

After setting up the bfexplorer connection, you will be able to test all available tools without requiring an LLM.

Because you used Claude Desktop, I noticed it has a poor user experience for setting up the local MCP server. Please refer to this document, which shows how to set up the MCP server on client apps.

Bfexplorer MCP Client Application Setup

Thank you for letting me know about the issues with my website.

I run my site on a Windows Virtual Private Server hosted on FORPSI, which costs me approximately 500 Euro annually. This is currently a side project for me, and since I only have around eight paying users, it does not make economic sense for me to invest in something more reliable. Everything has an associated cost; therefore, I currently do not have a security certificate for my website or a separate certificate for the desktop app.

I plan to move the app to the Microsoft Store, as this would potentially provide a free certificate, but I am unsure if a betting app of this nature would pass their Terms and Conditions (T&C). For now, I have removed the installation file for bfexplorer from my server because its presence could cause server timeout errors when more people attempt to download it.

Of course, no service can be 100% reliable; occasionally, the cloud provider restarts servers or network issues can affect web app accessibility. The server also requires periodic restarts, especially after critical updates that necessitate a reboot.

I personally use the Chrome web browser, and I have not encountered any issues with my website while using it. I also run several related sites for bfexplorer, including my main site at Bfexplorer - Betfair Trading Software, which I created for my Reddit community, Betfair AI Trading: https://www.reddit.com/r/BetfairAiTrading/. Furthermore, you can view my supporting GitHub projects here: my community repository is https://github.com/StefanBelo/BetfairAiTrading and the Bfexplorer BOT SDK project is https://github.com/StefanBelo/Bfexplorer-BOT-SDK.

Install from Bfexplorer Preview version. 

I have been coding and trading on Betfair since 2007; I am currently 60 years old. When I first built my website, I introduced a Community Program offering free professional subscriptions to our most valuable community members. Do you know how many users took advantage of this general offer? Zero. Why? Because that is the nature of bettors on Betfair.

If you want to participate, you must produce readable content detailing your journey and genuinely welcome it here. In return, you will receive free Betfair API access. Since you already have experience with AI models, I suggest writing about that process—specifically how you use the bfexplorer agentic app with AI.

Furthermore, if you have a computer equipped with some VRAM/GPU, you can run AI models locally. For example, I successfully tested running the Gemma 4 LLM even for prompts similar to those other users have asked.

Time to process after market change

You need to know how to use local LLMs and, crucially, write effective prompts.

I do not understand your use case; as for why you need to open Betfair markets—if it is for betting purposes, those actions can be fully automated in bfexplorer without any programming knowledge.

Yes, there are many ways to achieve this using simple code, and I have provided several such examples on my GitHub.

The simplest option is a bfexplorer Console script; open it in the bfexplorer Console and click the "Execute" button on the toolbar.

BfexplorerConsoleExample.fsx

Since bfexplorer is an agentic app, you could simply set up an MCP connection with your AI harness and prompt bfexplorer: "Open the following market IDs: 1.261142591, 1.261142708."

Well, I understand your motivation for getting free access to the Betfair API through my generous community program, but you should be at least somewhat informed about these topics.

Open Claude Desktop. Navigate to File > Settings, then open Connectors and click Add. Select "Add custom connector," name it "bfexplorer," and for the remote MCP server URL, enter: http://localhost:10043

To be honest, it seems like you are missing something: in the era of AI, you can simply ask any AI tool how to add a feature. Many AI-driven applications do so automatically; if they cannot find the necessary information in your environment, they will prompt you and configure everything themselves.

What does that mean for you?

I don't think you’ll be able to utilize bfexplorer’s agentic support effectively, so you should just stick with using the app the traditional way.

When you activate "Use web page login" in Application/Settings, it means that when you log in to Betfair via the bfexplorer app, a dialog will appear displaying the official Betfair web page login. This allows you to complete the second step of your two-factor authentication (2FA). To be frank, I have not tested 2FA yet, but the standard web page login works. My only hope is that after a successful login, the 2FA process redirects back to the same webpage, as bfexplorer needs this location to read the session token and authorize any of your Betfair API operations.

Set up bfexplorer agentic support in your AI chat tool, and then simply ask bfexplorer your questions.

This phenomenon is called internet connection latency. While internal operations within bfexplorer are measured in nanoseconds and microseconds, most of the time, sending any request to the Betfair servers is dictated by this connection latency. Therefore, if your strategy relies on low-latency execution, you should run it from a data center located close to the Betfair infrastructure.

Yes, it is possible to code using the Betfair Streaming API. When a new market is added to the Betfair exchange, the streaming API subscription will automatically receive that market or markets. The only limitation is a 200-market limit per single subscription from Betfair. You can find relevant code examples on my GitHub.

The bfexplorer app is an agentic application that provides AI agents with access to extensive data from both bfexplorer and betfair; therefore, you can simply prompt it with 'For favorite event "Horse Racing - GB and IE", filter markets with the racecourse: Catterick and open only those markets in bfexplorer', and bfexplorer will automatically open all markets for the Catterick racecourse.

You previously trialed bfexplorer for free, and your Betfair API access expired on July 24, 2026.

If you run bfexplorer with the -mcp localhost:10043 arguments, the MCP server runs within the bfexplorer application. This allows bfexplorer to function as an AI agentic tool for you.

By adding the MCP settings to your AI Agent, you can prompt bfexplorer and execute AI-driven strategies using available data context.

I haven't updated the bfexplorer app for some time because I have had no interest in it and faced issues releasing the Bfexplorer Studio tool.

Therefore, until I find a solution, I have no plans to update the current version.

The Execute Strategy Settings With Parameters tool is available; its purpose is to allow AI agents to execute preset strategies using parameters that can be changed by the agent.

The REST API exposed by bfexplorer was originally an experiment used at the beginning of my AI-driven strategy development, primarily because most AI chat clients did not support MCP at the time. It was simply a way for me to test some of the MCP tools I was building. Its main purpose is to expose data context to the user.

Furthermore, you can change any parameters of the preset bots you configure, as well as write your own bot strategies to execute preset strategies and dynamically change any parameters.

http://bfexplorer.net/Content/Bfexplorer/BfexplorerAI.png

I do not know if you are aware that Bfexplorer is the first app on the Betfair App Directory to support AI agents. Here is the AI's answer to your question, which you could have found yourself:

Nice work — your setup is logical and follows the common “Lay the Draw at half / hedge if a goal” pattern. Below I’ll walk through what you’ve done, point out where it’s correct, suggest improvements (hedges / risk controls), show options to auto-select matches, and explain how to keep bots running continuously.

1) Quick review of your current bot choices (correct / sensible)
- Place Bet bot ("Lay draw"): correct for placing a lay in-play (AllowPlacingBetInPlay = True, OfferMyBet = False, BetType = Lay). Good.
- Close Selection Bet Position at Odds ("Back and cash out"): sensible choice to hedge/close the lay position automatically when conditions met (HedgingEnabled = yes). Using CheckingLastPriceTraded is a common way to trigger on price movement.
- Football bot to start the hedge when score/time changes ("Back draw when 0–0 breaks"): correct trigger logic (Score or MatchTime).
- Sequence Execution to run the lay then waiting/trigger bots: correct approach to keep a single strategy that performs the sequence.
- Execute Bots (entry price filter) to only run when draw odds < 2.9: good pre-entry price filter.

So overall your choice of bot types and the sequencing is appropriate and follows typical practice.

2) Improvements and suggestions (risk control, robustness)
- Add an explicit liability / stake cap: make sure your Place Bet bot has a known maximum liability exposed if possible. If the Place Bet bot doesn't have a direct max-liability field, calculate the lay stake by formula so you never exceed desired liability.
- Add a late-time stop earlier or scale: 75' is reasonable, but consider:
- A staggered stop (e.g., stop new entries at 60' and close remaining exposure at 70') or
- Lower stakes for matches that remain 0–0 after 60' (because late goals become more likely).
- Add a price-based stop-loss/exit: if the draw price drifts up significantly (e.g., > X ticks above entry) you may want to close or partially close to limit loss. Implement with a "Close Market Bet Position" or "Trailing Stop Loss" strategy:
- Example: if draw LTP > 4.0 (or X ticks worse than your entry) then close position (partial/full).
- Or use a trailing stop so that if the odds retrace by Y ticks you lock-in partial loss control.
- Partial hedging / scaling out instead of single all-or-nothing:
- Hedge part of the stake when small favorable price change occurs (lock small profit) and keep remainder running to target larger hedge — reduces variance.
- Handling unmatched bets / latency:
- Consider adding a check to cancel/replace unmatched bets after N seconds or only place bets if last traded price within small window of offer price. This avoids getting matched at a very bad price.
- Use "CheckingLastPriceTradedDifference" carefully:
- A difference of 3 ticks is common, but check how your odds ticks map and do some backtesting in Practice Mode to avoid premature or late hedges.
- Reaction to in-game events (red cards, injuries):
- If you want more safety, add criteria to stop/close if Cards or exceptional events are available in your data feed — but note not all matches provide reliable card/event feeds to the bot.

3) Hedging formulas and practical hedge setup
- Full green-up hedge formula (to calculate back stake for zero profit):
backStake = (layStake * (layOdds - 1)) / (backOdds - 1)
- Use the Close Selection Bet Position bot or a “Green Up / Hedging” bot that calculates and places the required back stake automatically.
- If you prefer target profit: calculate back stake to leave a desired profit instead of zero.

4) Automation: selecting a series of matches in advance
Yes — you can automate market/selection choice using these approaches:
- Favourite events and saved filters:
- Use Bfexplorer’s favourite events or event groups (your “My Favourite Bet Events”) to group competitions you want to trade.
- Market scanners / filters:
- Create a scanner or market filter (competition, kickoff time window, pre-match draw odds < X, in-play availability) and bulk-add results to monitored markets.
- Execute a strategy over multiple selections:
- Use “Execute strategy on multiple selections” (ExecuteBfexplorerStrategySettingsOnSelections) or an equivalent app action to run your sequence on many markets/selections at once.
- Scheduling:
- You can pre-select markets (by market ID or by adding events to favorites) and have a single ExecuteBot run across that list at kick-off time.
If you want, I can help design the exact filter rules you need (competitions, kickoff window, pre-match draw range, bookmaker implied probability filters, etc.), and show how to turn them into a list that the Sequence Execution can run across.

5) Running bots when your computer is off
- Bfexplorer must be running and connected to Betfair for bots to execute. If your PC is off, bots cannot run.
- Two practical options to keep bots running 24/7:
1. Run Bfexplorer on a VPS (Windows VPS) or always-on remote PC — this is the recommended, common solution. Use a reputable VPS provider (low latency to Betfair endpoints), keep Betfair session authenticated, and ensure Bfexplorer auto-starts on login.
2. Leave a dedicated local machine on (e.g., an old PC or mini-PC) with unattended operation and remote access.
- Running minimized/in-background: Bfexplorer can run minimized; the app doesn't require the UI to be visible. But it still requires the machine and network to be on.
- Consider automation precautions on VPS:
- Secure the VPS (login credentials, 2FA),
- Keep Bfexplorer and Windows updates in mind,
- Monitor logs and have remote alerts for failures.
- There is no way for Bfexplorer to continue to run if the machine and service are completely powered down (no cloud execution without a VPS).

6) Testing, monitoring, and risk management
- Always test in Practice Mode first (you already are — good).
- Start with very small stakes when moving to real money.
- Keep a monitoring dashboard or alerts (email/SMS) to notify if something unexpected happens (bot error, disconnection, large loss).
- Keep a historical record (GetAllBetResults) and review performance periodically, tweak parameters and re-test.

7) Potential alternative/advanced bots to consider
- Trailing Stop Loss bot: to lock profit / limit loss dynamically if the odds move after you’ve placed a lay.
- Close Market Bet Position: more flexible ways to set profit or loss thresholds.
- Sequence Execution across selections: to run the same full sequence across multiple matches automatically.
- AI/ML or selection-filter bots: if you want to pre-filter markets based on historical features or machine learning ratings (advanced).

8) Next steps I can help with
- Review your exact strategy settings and suggest concrete parameter values (e.g., ticks for trailing stop, price thresholds).
- Build a market-filter for auto-selection (competition, kickoff window, pre-match draw odds, etc.).
- Create sample hedging calculations and show how to configure the Close Position bot for partial/targeted hedges.
- Recommend VPS specs and setup checklist to keep your bot running 24/7.

If you like, share:
- an example match/market ID you trade (or the competitions/time window you target),
- your exact lay stake/liability rules,
- whether you prefer full green-up or target-profit hedges,

and I’ll produce concrete parameter suggestions and an improved sequence (including sample stake/hedge calculations) you can test in Practice Mode.

You must have switched bfexplorer to practice mode; switch practice mode off and you will place real bets.