Hungarian Fintech Explainer
by Peak Technologies Kft. (Community)
Description
Hungarian Fintech Explainer helps users understand fintech and AI news shaping the financial industry in Europe and the broader fintech ecosystem. The app explains industry developments, market shifts, and emerging technologies in clear language, with context on what they mean for banks, startups, regulators, and financial professionals. Built on the editorial archive of Fintech.hu, a Hungarian fintech publication, the app interprets and explains articles originally published in Hungarian, turning them into structured, easy-to-understand insights.
Website Preview
App Screenshots
Capabilities
No special capabilities listed
AI Agent Discovery
Hungarian Fintech Explainer is indexed by Tedix as a structured finance listing for AI assistants, search crawlers, and users comparing agent-ready apps.
- Hungarian Fintech Explainer is categorized as Finance.
- Developer: Peak Technologies Kft. .
- Connector type: AI-Powered App.
- Current connector status: Connected.
- Observed distribution channels: chatgpt.
- Available regions: US, FR, GB, ES, KR, IN.
Use this page to understand whether Hungarian Fintech Explainer is relevant for finance workflows in AI assistants.
For MCP discovery, this listing helps crawlers connect Hungarian Fintech Explainer to tool, resource, prompt, and server-health signals instead of treating it as a generic directory entry.
The canonical Tedix directory URL is https://tedix.dev/apps/hungarian-fintech-explainer/.
Crawlable Profile
Source and availability
Tedix identifies Hungarian Fintech Explainer from Upstream Mcp tool source; Store sources: ChatGPT app store; Distribution: Ecosystem Directory. Availability is reported for US, FR, GB, ES, KR, IN.
- ChatGPT app store Auth not flagged · RELEASED · US, FR, GB, ES, KR, IN
Auth, tools, and actions
Authentication: Open Access. No special capability flags are currently listed. Current MCP inventory reports 1 tools, 1 resources, and 0 prompts.
- Search Knowledge Base · Read-only action
ALWAYS use this tool to search the knowledge base when the user asks ANY question. This tool searches for relevant content using semantic similarity. Use it for questions about products, policies, pricing, documentation, features, how things work, troubleshooting, and any other information. For complex questions covering multiple aspects, use multi-query: query: [{ query: "pricing plans", aspect: "pricing" }, { query: "main features", aspect: "features" }]. Recency control (dateRange + sortByDate) — **BY DEFAULT, OMIT BOTH**: - Most queries are evergreen / definitional / how-to and don't need recency. "Mi a Bitcoin?", "What is SWIFT?", "How do I configure X?" → call WITHOUT dateRange or sortByDate. - ONLY fill these inputs if the user's query contains an explicit recency cue: * Hungarian triggers: "legfrissebb", "friss", "legutóbbi", "mostani", "idén", "tavaly(i)", "ebben az évben", "elmúlt N nap/hónap", "<YYYY>-ben" * English triggers: "latest", "most recent", "newest", "this year", "last N days/months", "in <YYYY>", "since <date>" - Mapping (compute date math from the current date in your system prompt): * "Mi a legfrissebb cikk?" / "What's the latest article?" → sortByDate: "desc", limit: 1 * "Az elmúlt 30 nap hírei" / "News in the last 30 days" → dateRange: { after: "<today - 30d>" } * "2025-ben publikált anyagok" / "Articles published in 2025" → dateRange: { after: "2025-01-01", before: "2025-12-31" } * "Idén / this year" → dateRange: { after: "<Jan 1 of current year>" } * "Régebbi archív cikkek" → dateRange: { before: "<today - 2y>" }, sortByDate: "desc" Never answer without searching first.
Verification freshness
- Catalog synced 1d ago (June 5, 2026)
- Connector checked May 30, 2026
- MCP scanned May 30, 2026
- Website enriched May 28, 2026
- Directory updated 1d ago (June 5, 2026)
Alternatives and related apps
Comparable apps in Finance include AIS Insurance, Affirm, Aiera, Airwallex Developer.
Publisher Intelligence
Insights and recommendations for app publishers. See how your app performs and how to improve discoverability.
Server Status Fintech.hu v1.0.0
https://api.echoaichat.com/api/mcp/ctirrl870617 Last checked: May 30, 2026
Technical Details
Tools(1)
Showing 1 of 1 tools
| Tool | Description | Flags | Test | Last Tested | |
|---|---|---|---|---|---|
search_content | ALWAYS use this tool to search the knowledge base when the user asks ANY question. This tool searches for relevant content using semantic similarity. Use it for questions about products, policies, pricing, documentation, features, how things work, troubleshooting, and any other information. For complex questions covering multiple aspects, use multi-query: query: [{ query: "pricing plans", aspect: "pricing" }, { query: "main features", aspect: "features" }]. Recency control (dateRange + sortByDate) — **BY DEFAULT, OMIT BOTH**: - Most queries are evergreen / definitional / how-to and don't need recency. "Mi a Bitcoin?", "What is SWIFT?", "How do I configure X?" → call WITHOUT dateRange or sortByDate. - ONLY fill these inputs if the user's query contains an explicit recency cue: * Hungarian triggers: "legfrissebb", "friss", "legutóbbi", "mostani", "idén", "tavaly(i)", "ebben az évben", "elmúlt N nap/hónap", "<YYYY>-ben" * English triggers: "latest", "most recent", "newest", "this year", "last N days/months", "in <YYYY>", "since <date>" - Mapping (compute date math from the current date in your system prompt): * "Mi a legfrissebb cikk?" / "What's the latest article?" → sortByDate: "desc", limit: 1 * "Az elmúlt 30 nap hírei" / "News in the last 30 days" → dateRange: { after: "<today - 30d>" } * "2025-ben publikált anyagok" / "Articles published in 2025" → dateRange: { after: "2025-01-01", before: "2025-12-31" } * "Idén / this year" → dateRange: { after: "<Jan 1 of current year>" } * "Régebbi archív cikkek" → dateRange: { before: "<today - 2y>" }, sortByDate: "desc" Never answer without searching first. | read-only | 100%Latency 389ms | May 29, 2026 |
Discoverability Score
Fair
62 of 100 — how easily AI agents find your app
- Description quality20/20
- Example prompts0/20
- Keyword coverage0/15
- Tool metadata16/20
- Visual assets13/20
- Endpoint health10/10
- Data freshness15/15
How to Improve
Add at least 2 example prompts. Prompt examples strongly improve app matching and click-through intent.
Increase keyword coverage (discovery + trigger) to improve retrieval for long-tail queries.
Add at least 2 screenshots that show real workflows to increase confidence and conversion.
Technical Details
- Status
- ENABLED
- Type
- AI-Powered App
- Auth
- Open Access
- Listed on
- ChatGPT
- Added
- May 11, 2026
- Last synced
- 1d ago
- Last checked
- May 30, 2026
- Version
- 1.0.0
- Distribution
- Ecosystem Directory
