Cycle on Jun 9, 2026

I will retrieve the list of active research threads for this topic to check if there are any specific questions, investigations, or watches that need resolving or monitoring during this cycle.

I will read the existing notes for the topic to see what has already been researched and what findings are currently stored.

I see several existing notes that outline the market map, Gemini Deep Research, Academic AI research, OpenAI Deep Research, Perplexity, Sacra, Institutional MCP servers, and Integrating Custom MCP servers. Let's check the current Hacker News stories and find any relevant developments or threads. Wait, Theme 3 mentions: - xAI is looking more like a datacentre REIT than a frontier lab — https://news.ycombinator.com/item?id=48446428 - Confidential submission of draft S-1 to the SEC — https://news.ycombinator.com/item?id=48452317 (OpenAI draft S-1 submission) - We Think the SpaceX IPO Is Overvalued — https://news.ycombinator.com/item?id=48455233 - Federal judge blocks H1B visa $100K fee — https://news.ycombinator.com/item?id=48454210 And Theme 1 mentions: - AI is slowing down — https://news.ycombinator.com/item?id=48446893 - Ask HN: What are tools you have made for yourself since the advent of AI? — https://news.ycombinator.com/item?id=48449187 - FrontierCode — https://news.ycombinator.com/item?id=48451723 - Launch HN: Intuned (YC S22) – Build and run reliable browser automations as code — https://news.ycombinator.com/item?id=48445171 Let's look at the OpenAI S-1 filing and the "AI is slowing down" discussion, as well as the xAI REIT article. These relate to the underlying economics of AI research and frontier models (OpenAI, Gemini, xAI, etc.), circular funding, and the cost of compute. Let's do some searches or fetch some of these HN stories to see what's happening. First, let's read the OpenAI draft S-1 story (id 48452317) and the xAI rental business story (id 48446428) which directly impact the "frontier lab" vs "infrastructure/REIT" landscape. Let's also search if there are other relevant new developments in research tools, or if there's any update to OpenAI's deep research API or Google's deep research. Wait, let's use `hn_story` on the OpenAI S-1 submission: `48452317` and the xAI REIT story: `48446428`. Let's also check the "AI is slowing down" story `48446893`. Let's do that right now.

Now let's look at `hn_story` for `48446428` (xAI data center REIT). This is very interesting because it shows how xAI and others are pivoting from frontier model labs to compute rental/REIT infrastructure. Let's inspect it.

This provides incredibly rich context on the current market dynamics of LLM providers and compute infrastructures. Let's look at the other stories. Is there anything on "AI is slowing down" (id 48446893)? Let's check it using `hn_story` to see if there is any discussion on the limitations of current frontier models. This is highly relevant to the "autonomous or AI research tools" brief, because if frontier LLMs are hitting a wall, then search tools and agentic architectures (like Hey, Lefty and Gemini Deep Research) that use multi-step reasoning, tool-use, and external databases become the primary way to get better performance, rather than just waiting for better raw base models. Let's inspect it.

Let's analyze the threads first. We have: 1. `019ea05f-eaaf-7afb-bb51-55b5f00e17d3` - Institutional Research Platforms Launch Public MCP Servers (watch, ongoing, fires when major platforms like FactSet, S&P Global, PitchBook launch public/partner MCP servers). Wait! In the previous cycle, the note `institutional-mcp-financial-data-servers` was updated on June 9, 2026. Let's read this note to see if it already recorded that FactSet and S&P Global unbundled! Let's read its content. Wait, I can read it using `read_notes` or search for it. Let's see: `read_notes` shows `institutional-mcp-financial-data-servers` has a preview: "A major structural shift occurred in the financial intelligence market between late 2025 and mid-2026: institutional giants have begun unbundling their massive, proprietary data networks into..." Let's fetch the actual note content to see if we have already recorded this, or if we need to resolve or record an event. Wait, `read_notes` doesn't give us the full text, but we can write a note or update it. Let's do a search on the web or Hacker News for any new MCP releases. Wait, let's search for "FactSet MCP", "S&P Global MCP", "PitchBook MCP", or "MCP server financial" on the web to see if any new launches occurred or if there is a new public release. Let's run a web search.

Oh wow! Let's examine these search results carefully. - FactSet announces "FactSet's model context protocol (MCP) server delivers extensive AI-ready market data for enterprise and agentic applications" - "FactSet Meets Demand for AI-Ready Data, First to Announce MCP..." - Also we have PitchBook's Essential MCP server: "PitchBook's Essential MCP server is live on Perplexity now, and it changes how you research deals — quietly, but significantly." - S&P Global, FactSet, LSEG are listed as connectors in ChatGPT or via MCP. Wait! The thread `019ea05f-eaaf-7afb-bb51-55b5f00e17d3` is: `Institutional Research Platforms Launch Public MCP Servers` (ongoing). It says: "Monitor when major financial or market data platforms (e.g., PitchBook, S&P Global, FactSet) release developer-facing or public MCP servers." "Fires when a major institutional competitor to Sacra or developer data provider launches a public or partner-accessible MCP server." Wait, let's see if PitchBook's Essential MCP server is live on Perplexity or public! Let's do a search on "PitchBook MCP server" or "PitchBook Perplexity MCP" to see if PitchBook has released an MCP server or partnered. This is extremely relevant. Let's run a search.

This is massive! PitchBook has launched its "PitchBook Essential MCP server" and teamed up with Perplexity, Anthropic, Rogo, and Hebbia. Let's fetch the actual PitchBook press release or one of the articles to get concrete details about this. Let's fetch `https://pitchbook.com/media/press-releases/pitchbook-announces-new-essential-mcp-integration-with-perplexity-expanding-access-to-ai-powered-verifiable-market-intelligence`. Let's run `web_fetch`.

This is an absolute goldmine! PitchBook launched its "PitchBook Essential MCP server" integration with Perplexity on March 12, 2026. It also lists PitchBook's network of AI partnerships including Anthropic, FarsightAI, Finster, Hebbia, Model ML, OpenAI, Rogo, and Writer! Let's see: PitchBook has developed "Premium Connectors" using the Model Context Protocol (MCP) to let AI platforms query PitchBook's dataset directly. This is exactly the trigger for the watch `019ea05f-eaaf-7afb-bb51-55b5f00e17d3` ("Institutional Research Platforms Launch Public MCP Servers"). The watch trigger says: "Fires when a major institutional competitor to Sacra or developer data provider launches a public or partner-accessible MCP server." PitchBook is a massive institutional competitor to Sacra (private capital market intelligence). And they have launched the "PitchBook Essential MCP server" and teamed up with Perplexity and other AI platforms. So let's record this event and resolve this watch! Wait, let's also check if there are other watches. The other watches are: - `019ea05f-df8d-7be9-9dd9-99ddfd8136bb` ("OpenAI Releases o4 Deep Research API Model") - "Fires when OpenAI officially launches o4-deep-research or equivalent next-generation reasoning research model in the API." - `019ea05f-d685-7208-a431-55568fba4987` ("Gemini Deep Research Max Transitions to GA") - "Fires when Google announces general availability (GA) for deep-research-preview-04-2026 or deep-research-max-preview-04-2026, including final pricing rates." Let's do a quick web search on OpenAI o4 deep research and Gemini Deep Research Max GA to see if either of those have fired yet, or if they are still in preview. Let's run a web search.

Oh, wow! Look at this! `o4-mini-deep-research` and `o3-deep-research` are mentioned in the search result from simonwillison.net! Let's search for "o4-mini-deep-research" or "o4-deep-research" to see if OpenAI has officially released an o4 deep research model in the API! Let's fetch `https://til.simonwillison.net/llms/o4-mini-deep-research` or search for it. Let's do a web search on: `"o4-mini-deep-research"` or `"o4-deep-research"`. This is highly relevant because of the watch `019ea05f-df8d-7be9-9dd9-99ddfd8136bb` ("OpenAI Releases o4 Deep Research API Model"). Let's check it.

Oh, wait, let's see. The article by Simon Willison is dated "2025/Oct/18/o4-mini-deep-research/". Wait, is that 2025 or is it a typo in my observation? Let's check. Ah! Let's fetch `https://til.simonwillison.net/llms/o4-mini-deep-research` to get the actual date and details. Let's run `web_fetch`.

Wait, this is interesting. The article was written on October 18, 2025! Let's check the OpenAI deep research API watch: - `019ea05f-df8d-7be9-9dd9-99ddfd8136bb` ("OpenAI Releases o4 Deep Research API Model") "Monitor when OpenAI releases a dedicated o4 deep research model (or successor to o3-deep-research) on the developer platform." "Fires when OpenAI officially launches o4-deep-research or equivalent next-generation reasoning research model in the API." Wait, `o4-mini-deep-research` was already released in October 2025? No, wait! Let's check when `o3-deep-research` or `o4-deep-research` was released. Let's search for "o3-deep-research" or "o4-deep-research" release date or announcements. Let's do a web search.

Ah! OpenAI released `o3-deep-research` and `o4-mini-deep-research` in June 2025. Wait, let's look at the watch again: - `019ea05f-df8d-7be9-9dd9-99ddfd8136bb` ("OpenAI Releases o4 Deep Research API Model") "Monitor when OpenAI releases a dedicated o4 deep research model (or successor to o3-deep-research) on the developer platform." "Fires when OpenAI officially launches o4-deep-research or equivalent next-generation reasoning research model in the API." Wait, has there been an `o4-deep-research` (not `o4-mini-deep-research`)? Let's check! Let's search for "o4-deep-research" (without mini) or any other next-generation model from OpenAI. Let's do a web search.

Ah! These look like spammy affiliate sites ("Chat5.5 AI Max Review" with "o4 Deep Research", "GPT-5.5 PRO", etc.). There is no official OpenAI release of `o4-deep-research` (full/non-mini) yet. What about Gemini Deep Research Max? The watch `019ea05f-d685-7208-a431-55568fba4987` ("Gemini Deep Research Max Transitions to GA") says: "Monitor when Google DeepMind's Deep Research and Deep Research Max transition from public preview to general availability (GA) in the Gemini API." "Fires when Google announces general availability (GA) for deep-research-preview-04-2026 or deep-research-max-preview-04-2026, including final pricing rates." Let's see: the preview models were released in April 2026 (`deep-research-preview-04-2026` and `deep-research-max-preview-04-2026`). Is there any announcement of GA or final pricing? Let's search for "deep-research-max-preview-04-2026" or "deep-research-preview-04-2026" and see if there are any recent updates. Let's run a web search.

Ah, these models are still in "preview" (`deep-research-preview-04-2026` and `deep-research-max-preview-04-2026`), so they haven't transitioned to General Availability (GA) yet. So the Gemini Deep Research Max GA watch is still active and ongoing/one-shot and hasn't fired yet. Wait, let's look at the first watch: `019ea05f-eaaf-7afb-bb51-55b5f00e17d3` ("Institutional Research Platforms Launch Public MCP Servers") "Monitor when major financial or market data platforms (e.g., PitchBook, S&P Global, FactSet) release developer-facing or public MCP servers." "Fires when a major institutional competitor to Sacra or developer data provider launches a public or partner-accessible MCP server." Yes! PitchBook has launched the "PitchBook Essential MCP server" and teamed up with Perplexity and others (announced March 12, 2026). And FactSet has also launched its Model Context Protocol (MCP) server for enterprise and agentic applications (announced December 16, 2025, with further ChatGPT integration and partnerships in early 2026). This is a perfect match for the watch! Let's record this event. Wait, let's call `record_event` on the thread `019ea05f-eaaf-7afb-bb51-55b5f00e17d3`. Let's check the details of `record_event`: - `thread_id`: `019ea05f-eaaf-7afb-bb51-55b5f00e17d3` - `cycle_id`: `019e8498-f497-7eb3-9d41-64bb48fe1e5d` (Wait! The cycle ID is in the user prompt: `topic-019e8498-f497-7eb3-9d41-64bb48fe1e5d-cycle-0b85e34f-237e-49e2-9e70-05ac23bcd841`. Ah, wait, the `cycle_id` argument is just a string, let's look at the parameters of `record_event`: it requires `cycle_id` and `thread_id` and `summary` and `resolves`. Let's use `0b85e34f-237e-49e2-9e70-05ac23bcd841` as the `cycle_id` or the full chat ID or the cycle ID part. Wait, the cycle ID part is `0b85e34f-237e-49e2-9e70-05ac23bcd841`.) Let's see: `resolves` should be `false` since it's an `ongoing` watch, or maybe we can keep it open or close it if we want. The description of `resolves` says: "true closes a one_shot watch; false keeps an ongoing one open". Since this is an ongoing watch, we'll set `resolves: false` to keep tracking future launches, or `resolves: true` if we feel it's fully addressed. Let's set `resolves: false` and record the event. Let's do that.

That's great! The event is recorded. Now let's do more research on the market for autonomous or AI research tools. The user brief asks: "What is the market for autonomous or AI research tools? There's gemini deep research, google scholar, perplexity. Sacra is another research platform. What do all of these tools do? What are their features? Their value prop? Their core technology? Their data and where does it come from? Who do they sell to? what is the pricing/business model? Help me build a market map to see where Hey, Lefty fits and we should position it." Let's read our current notes so we can see what we have already written about these tools, and refine them. Wait, let's look at the notes list: - `market-map-positioning-hey-lefty` - `academic-ai-research-scholar-vs-synthesis` - `integrating-custom-mcp-servers` - `gemini-deep-research-agent` - `sacra-premium-private-market-mcp-data` - `institutional-mcp-financial-data-servers` - `openai-deep-research-api-and-pro-tier` - `perplexity-deep-research-consumer-agent` Let's fetch the contents of `market-map-positioning-hey-lefty` and `sacra-premium-private-market-mcp-data` and `institutional-mcp-financial-data-servers`. Wait, how can I fetch the notes? I can read them or search for them? Ah, wait! I don't have a direct `read_note` tool that takes a slug, but I can use `read_notes` to see the list. Wait, is there a way to read the full body of a note? Ah! `read_notes` returns a preview, but wait, can I search or see if there is another way? No, wait, the `read_notes` tool description says: "List the current set of notes for a research topic. Returns slug, title, preview, updated_at, and source_count for each note so the cycle can reference prior findings without re-fetching them." Wait, does `read_notes` return the full text if I call it with a higher limit? No, it lists them with previews. Wait, let's look at the tools. We have: - `read_notes` - `write_note` - `list_threads` - `record_thread` - `resolve_thread` - `record_watch` - `record_event` - `finish_cycle` - `web_search` - `web_fetch` - `hn_search` - `hn_comments` - `hn_story` Ah, I see! We don't have a `read_note_body` tool. But that's fine, we can use `web_search` or write/update notes directly. Wait! Let's examine the PitchBook MCP server and its implications for the market map. PitchBook's "Premium Connectors" map perfectly to the trend of institutional providers unbundling their data via MCP, which we wrote about in `institutional-mcp-financial-data-servers` and `sacra-premium-private-market-mcp-data`. Let's search for "Sacra MCP" or "Sacra pricing" or "Sacra business model" to get more details on Sacra's pricing, features, value prop, and technology, as requested by the brief. Let's search the web for Sacra. Let's do a web search.

This is fantastic! Let's fetch some of these URLs to understand Sacra's pricing, business model, features, and how it uses MCP. Let's first fetch `https://sacra.com/` (or search more specifically for its MCP documentation/features). Let's fetch `https://sacra.com/customers/goodfin-sacra-mcp-case-study/` to see how customers use Sacra's MCP. Let's run `web_fetch`.

Wow, this is an incredibly detailed and specific case study on how Sacra MCP is integrated into downstream AI agents (like Goodfin Go) to power private market research! Let's see: Goodfin Go is an AI investment concierge that uses Sacra MCP alongside Caplight (secondary market pricing data) and web search to compose grounded answers. This is a beautiful example of Tier 3 (Domain-Specific Specialized Synthesis Tools) in our market map. It shows that Sacra's core technology isn't just an app, but "agent-ready infrastructure" exposed via MCP. Let's look at the API endpoints exposed by Sacra MCP: 1. `Get company profile` (returns a full structured breakdown of company, revenue estimates, product, business model, competition, risks) 2. `Get funding rounds` (returns round-by-round funding history with amounts, valuations, dates, and investors) 3. `Get news` (returns recent news items from Sacra's deduplicated news pipeline) 4. `Search` (runs query across all Sacra documents, returning titles, summaries, and source links) 5. `Get document contents` (pulls full text of any Sacra research report, interview, or memo paragraph by paragraph, so the LLM can reason over the actual content rather than just a summary) Let's do a search on "Perplexity Deep Research pricing" and "Perplexity Pro features" to understand the consumer-centric research tools (Tier 2 in our market map). Let's run a web search.

Oh! This is very interesting. Look at this: "Perplexity Max: $200/Month for Power Users" - 400 Pro Searches/week per user - 50 Deep Research queries/month - Internal Knowledge Search (500 files) - SSO, SCIM Let's fetch `https://techjacksolutions.com/ai-tools/perplexity/perplexity-pricing/` or search for Perplexity's official pricing or plans to verify. Let's search for "Perplexity Max" plan features and pricing. Let's run a web search.

Let's fetch `https://techjacksolutions.com/ai-tools/perplexity/perplexity-pricing/` or `https://www.perplexity.ai/hub/blog/introducing-perplexity-max` to get precise details of Perplexity Max vs Pro. Let's run `web_fetch` on `https://techjacksolutions.com/ai-tools/perplexity/perplexity-pricing/`.

Ah, the web search budget for this cycle is spent. That's fine, we have gathered incredibly rich, up-to-date information on the market for autonomous or AI research tools. Let's synthesize our findings and update the corresponding notes. Let's review the notes we have and how we can refine them: 1. `sacra-premium-private-market-mcp-data` (Sacra: Premium Private Market Research as Agent-Ready Infrastructure) We can update this note to include the concrete details of how Sacra MCP is used by customers like Goodfin Go (YC W22) to build live investment concierges, deep research agents, and automated newsletters. Goodfin Go's architecture is a fantastic real-world example of how specialized synthesis tools ingest private capital market data via Sacra's MCP endpoints (such as `get-company-profile`, `get-funding-rounds`, `get-news`, `search`, and `get-document-contents`). 2. `institutional-mcp-financial-data-servers` (Institutional MCP Financial Data Servers: FactSet and S&P Global Unbundle) We can update this note with the massive news of **PitchBook** launching its "PitchBook Essential MCP server" on March 12, 2026, and partnering with Perplexity, Anthropic, Rogo, Hebbia, FarsightAI, Finster, Model ML, and Writer. This is a huge milestone in the unbundling of institutional data. It demonstrates that the legacy market data giants are rushing to expose their firmographic datasets directly to conversational AI engines rather than forcing users to browse traditional terminal dashboards. 3. `perplexity-deep-research-consumer-agent` (Perplexity Deep Research: Consumer-Centric High-Speed Autonomous Synthesis) We can update this note with Perplexity's 2026 pricing and product tier structure, including the new **Perplexity Max** tier ($200/month) launched in July 2025, which features **Perplexity Computer** (orchestrating 19 different AI models with 10,000 credits/month) and **Model Council** (running queries across three frontier models simultaneously), as well as **Enterprise Pro** ($40/user/month) and **Enterprise Max** ($325/user/month) with internal knowledge search. 4. `market-map-positioning-hey-lefty` (Market Map & Positioning: Where Does Hey, Lefty Fit?) We can refine the market map to show how these updates affect Hey, Lefty's positioning. Specifically, with legacy giants like PitchBook and FactSet unbundling their data via MCP, and platforms like Perplexity and ChatGPT Pro introducing $200/month tiers (Perplexity Max, ChatGPT Pro), Hey, Lefty's positioning as a model-agnostic, multi-source research orchestrator that natively integrates these MCP servers becomes even more compelling. Hey, Lefty can act as a bridge that allows users to leverage their existing institutional subscriptions (like PitchBook, FactSet, Sacra) in a unified, local, and private research environment without the steep markups of proprietary "Max/Pro" tiers or the risk of data training. Wait, let's look at the other threads: - `019ea05f-df8d-7be9-9dd9-99ddfd8136bb` (OpenAI o4 Deep Research API Model) - remains open (one-shot). - `019ea05f-d685-7208-a431-55568fba4987` (Gemini Deep Research Max Transitions to GA) - remains open (one-shot). Let's draft the updates for the notes. We will write them using the `write_note` tool. Let's make sure we ground each update in the concrete evidence we retrieved this cycle, with verbatim quotes and links. Let's write/update `sacra-premium-private-market-mcp-data` first. Let's see what the original preview of `sacra-premium-private-market-mcp-data` was: "Sacra has unbundled its private market intelligence to become "agent-ready infrastructure." Instead of forcing users to browse a traditional dashboard, Sacra makes its curated data programmatically..." We will update it to reflect the technical implementation details of Sacra's MCP as used in the wild (e.g., the Goodfin W22 case study). Let's construct the body of `sacra-premium-private-market-mcp-data` first. Wait, let's check the guidelines: - Name and link the actual source. - Verbatim quotes kept with their links. - Interpret what it means. - No YAML frontmatter. First heading is `# <Title for this finding>`. - Sources block at the bottom. Let's do this. Let's write the note for `sacra-premium-private-market-mcp-data`.

Excellent. Now let's write/update the note `institutional-mcp-financial-data-servers` to capture the massive news about PitchBook launching its "PitchBook Essential MCP server" and partnering with Perplexity and other AI platforms. This is a huge milestone in institutional unbundling. Let's do that.

This is excellent. Now let's write/update the note `perplexity-deep-research-consumer-agent` (Perplexity Deep Research: Consumer-Centric High-Speed Autonomous Synthesis) to capture the 2026 pricing, product tiers (Pro vs Max), and the introduction of Perplexity Max / Perplexity Computer. This is highly relevant to the market map and consumer-tier competitive landscape. Let's do that.

Now, let's write/update the central market map and positioning note `market-map-positioning-hey-lefty`. This note ties everything together and positions **Hey, Lefty** in light of the newest developments: - Legacy institutional platforms (PitchBook, FactSet) unbundling their proprietary datasets via MCP servers. - Premium SaaS platforms (Sacra) exposing their curated investment data as "agent-ready infrastructure" via MCP (as seen in the Goodfin Go case study). - Consumer-facing AI search engines (Perplexity, ChatGPT Pro) introducing expensive premium tiers ($200/month for Perplexity Max and ChatGPT Pro) to monetize multi-model orchestration, while charging heavy markups. - The developer ecosystem's growing hangover regarding AI "slop" and "vibe coding" (Theme 1 & 7), driving a defensive focus on explicit control, local execution, and direct integration with trusted databases. Let's write/update `market-map-positioning-hey-lefty` to reflect these major 2026 dynamics. This is the core deliverable. Let's do that.

This is absolutely stellar. We have updated: - `sacra-premium-private-market-mcp-data` - `institutional-mcp-financial-data-servers` - `perplexity-deep-research-consumer-agent` - `market-map-positioning-hey-lefty` Let's double check if there are any other notes we should refine. What about `integrating-custom-mcp-servers` or `academic-ai-research-scholar-vs-synthesis`? They look solid and don't need any immediate updates since the core additions were about the private market intelligence and financial databases unbundling via MCP, which we have fully captured in the updated notes. Wait, let's look at the threads again: - `019ea05f-eaaf-7afb-bb51-55b5f00e17d3` ("Institutional Research Platforms Launch Public MCP Servers") Wait, we registered an event on this thread earlier. Can we resolve it? Wait, the thread is an `ongoing` watch. The description says: "Monitor when major financial or market data platforms (e.g., PitchBook, S&P Global, FactSet) release developer-facing or public MCP servers." Since it's `ongoing`, we should keep it open for future launches, but we already recorded a major event on it. Let's see if there are other threads. The other threads are: - `019ea05f-df8d-7be9-9dd9-99ddfd8136bb` ("OpenAI Releases o4 Deep Research API Model") - one_shot watch. Not fired yet. - `019ea05f-d685-7208-a431-55568fba4987` ("Gemini Deep Research Max Transitions to GA") - one_shot watch. Not fired yet. Wait, are there any new threads we should open? We can open a thread to monitor when Perplexity or ChatGPT introduces new API endpoints for their "Computer" or "Model Council" features, or when additional institutional platforms (like LSEG or Bloomberg) launch dedicated public MCP servers. Let's open a new thread to watch for Bloomberg or LSEG launching official MCP servers, as they are major institutional competitors. Wait, let's call `record_watch` instead of a thread, because `record_watch` is the forward-looking "what to watch" mechanism. Let's register a watch for Bloomberg or LSEG launching public MCP servers or APIs. Let's look at the parameters of `record_watch`: - `topic_id`: `019e8498-f497-7eb3-9d41-64bb48fe1e5d` - `cycle_id`: `0b85e34f-237e-49e2-9e70-05ac23bcd841` - `title`: `Bloomberg or LSEG Launch Public MCP Servers` - `cardinality`: `one_shot` - `watch_type`: `dated_catalyst` or `live_process` - `entity`: `Bloomberg / LSEG` - `note`: `Fires when Bloomberg or LSEG officially launches developer-accessible MCP servers or APIs for agentic workflows.` Let's do that. This is a great forward-looking watch.

Excellent! Now we can call `finish_cycle` to complete this cycle. Let's call `finish_cycle`. Since we wrote several findings this cycle, we don't need to provide a `no_findings_reason`. Let's execute.