Meeting Title: Lead Nurturing Automation Sync Date: 2026-04-08 Meeting participants: Hannah Wang, Brylle Girang
WEBVTT
1 00:00:21.800 ⇒ 00:00:22.940 Hannah Wang: Hey.
2 00:00:23.490 ⇒ 00:00:26.830 Brylle Girang: Hello! Really sorry I missed our meeting earlier.
3 00:00:26.830 ⇒ 00:00:38.059 Hannah Wang: Oh, that’s okay. Nobody’s… Mmm… Okay, let me… Clean up everything, and…
4 00:00:38.580 ⇒ 00:00:39.280 Brylle Girang: Okay.
5 00:00:39.280 ⇒ 00:00:43.210 Hannah Wang: Show you… Screen.
6 00:00:56.910 ⇒ 00:01:05.140 Hannah Wang: So… I guess my initial request was, or the context that I gave you was for…
7 00:01:05.379 ⇒ 00:01:09.780 Hannah Wang: Basically setting up a skill that’ll help nurture
8 00:01:09.970 ⇒ 00:01:17.370 Hannah Wang: leads, and what I mean by that is… let me actually share my whole screen.
9 00:01:18.030 ⇒ 00:01:22.299 Hannah Wang: If I go to…
10 00:01:23.310 ⇒ 00:01:33.560 Hannah Wang: Robert’s LinkedIn, the go-to-market team runs a lot of campaigns that are centered around events. So, for example, we send
11 00:01:33.980 ⇒ 00:01:45.650 Hannah Wang: outbound messages… connection requests to people, and the messaging kind of looks like this. Like, hey, person, saw you’ll be at so-and-so event, would love to connect, and…
12 00:01:46.050 ⇒ 00:01:55.379 Hannah Wang: We found a lot of… a lot of success with this, because, like, yeah, a lot of people accept our connection request, but the bottleneck that we’re having is
13 00:01:55.560 ⇒ 00:02:03.830 Hannah Wang: Robert doesn’t really have time to nurture all these people, basically.
14 00:02:04.060 ⇒ 00:02:14.160 Hannah Wang: these are, like, marketing leads, but we want to nurture them if they’re in our ICP to be sales leads, so that they can enter our pipeline.
15 00:02:14.330 ⇒ 00:02:21.589 Hannah Wang: So the automation… the skill that I wanted to build was basically given
16 00:02:22.380 ⇒ 00:02:27.179 Hannah Wang: Like, a lead list, like this, for example.
17 00:02:29.380 ⇒ 00:02:40.100 Hannah Wang: like, if I feed it the name, the URL, the title of the job, and the company, I basically want cursor to…
18 00:02:40.200 ⇒ 00:02:49.729 Hannah Wang: spit out a message that sounds like Robert, and also will help drive towards booking a meeting with the lead.
19 00:02:49.730 ⇒ 00:02:50.370 Brylle Girang: Okay.
20 00:02:50.790 ⇒ 00:02:55.799 Brylle Girang: So, is it supposed to be, like, the first message? Or are these leads…
21 00:02:56.070 ⇒ 00:03:00.600 Brylle Girang: Have you already reached out to these leads, or are they just, you know, new leads?
22 00:03:01.120 ⇒ 00:03:18.689 Hannah Wang: it’ll be like this. These are new leads. Okay. I would love to connect. But before I continue on, I… I think… so I did build something, but it’s not using LinkedIn MCP or anything like that, and then Robert messaged me this morning and was basically like.
23 00:03:18.740 ⇒ 00:03:29.269 Hannah Wang: oh, I built something using, HeyReach, which is, like, an automation tool that we use to send out automated messages via LinkedIn. So,
24 00:03:29.470 ⇒ 00:03:34.739 Hannah Wang: I feel like he… did a workaround, so, I don’t…
25 00:03:35.350 ⇒ 00:03:40.940 Hannah Wang: I’m gonna put a pin in that request, but I still would like to connect
26 00:03:41.260 ⇒ 00:03:53.879 Hannah Wang: cursor to LinkedIn MCP, not for messaging purposes, but for another ask that I have, which is to build, like, an event
27 00:03:54.110 ⇒ 00:03:57.500 Hannah Wang: scraper skill in cursor, so…
28 00:03:57.760 ⇒ 00:04:13.509 Hannah Wang: I just gave you all that context because, like I said, we found a lot of success with people accepting our connection requests for different events. Whether or not we go to them or not, it doesn’t matter. As long as the event is
29 00:04:13.660 ⇒ 00:04:19.830 Hannah Wang: like, relevant to our company. We want to target them, so,
30 00:04:20.490 ⇒ 00:04:39.479 Hannah Wang: you can see here, like, we run campaigns, and a lot of them are conference-based, or event-based, as we like to say, and I want to build a skill that scrapes, like, Luma, for example, which is, like, a…
31 00:04:39.820 ⇒ 00:04:49.509 Hannah Wang: platform that people, like, host events on, or scrapes the internet, and I feel like
32 00:04:49.780 ⇒ 00:05:08.140 Hannah Wang: cursor is capable of doing that, but I also wanted to scrape LinkedIn. Like, you can see Robert’s main feed, like, a lot of people post, like, hey, I’m going to this event, or I’m hosting this event, and I just want to be able to get a list of all
33 00:05:08.240 ⇒ 00:05:21.780 Hannah Wang: Of those events, so that goes back to my question of connecting a LinkedIn MCP to Cursor. So I did do research and, like.
34 00:05:22.850 ⇒ 00:05:32.460 Hannah Wang: There are… there is, like, an official LinkedIn way to do it, where they do have an API.
35 00:05:37.980 ⇒ 00:05:39.069 Hannah Wang: I think…
36 00:05:39.600 ⇒ 00:05:57.429 Hannah Wang: somewhere here, like, there’s a link to it, and they have a bunch of APIs that we can call and stuff, but the problem with this one is that we need to be approved by LinkedIn, and I feel like the acceptance rate is pretty low, so we can’t use their official
37 00:05:57.630 ⇒ 00:06:09.280 Hannah Wang: like… API documentation or whatever. And then there is, like, other commercial APIs that… like, basically SaaS products.
38 00:06:09.580 ⇒ 00:06:17.430 Hannah Wang: that… People have built to help scrape LinkedIn on our behalf.
39 00:06:17.860 ⇒ 00:06:31.320 Hannah Wang: like, this is called Unipile, but obviously, like, we don’t want to pay for anything if we can build it ourselves, but I think this probably provides, like, what we would want, where
40 00:06:31.960 ⇒ 00:06:41.369 Hannah Wang: yeah, we can, like, pull from profiles or scrape messages or whatever. So there is this option that I found, and then…
41 00:06:41.580 ⇒ 00:06:50.480 Hannah Wang: Another one that I found was, like, someone built an MCP server Just… You know, on GitHub.
42 00:06:50.480 ⇒ 00:06:51.010 Brylle Girang: Yeah.
43 00:06:51.160 ⇒ 00:06:56.370 Hannah Wang: But I don’t know if this is, like, it can be hooked up to…
44 00:06:56.570 ⇒ 00:07:00.389 Hannah Wang: cursor, like, the example uses Claude, but…
45 00:07:00.920 ⇒ 00:07:08.050 Hannah Wang: yeah, I just don’t know, like, the tech… technical nitty-gritty behind everything, so that’s why when I said, like, oh, it…
46 00:07:08.260 ⇒ 00:07:17.399 Hannah Wang: the cursor said it’s hard to connect, like, I think because we can’t use the official LinkedIn one, and then there’s, like, all these other
47 00:07:17.810 ⇒ 00:07:18.700 Hannah Wang: I guess.
48 00:07:19.020 ⇒ 00:07:22.689 Hannah Wang: hacky ways to do it, but I just don’t know, like…
49 00:07:23.020 ⇒ 00:07:32.940 Hannah Wang: the architecture of everything, and how it’ll be set up, so I don’t know if it’s possible or not. So I’ll pause there, and let you kind of give your thoughts.
50 00:07:33.410 ⇒ 00:07:43.229 Brylle Girang: Yeah, yeah, I think it’s super clear. So, initially, you’re… the problem is that we need to, like, connect cursor to send messages to our leads, but since
51 00:07:43.270 ⇒ 00:07:58.230 Brylle Girang: Robert was able to find a workaround there. Our main problem now is try to use Cursor to, like, scrape LinkedIn or other platforms to gather more events, so then we can get more leads, right?
52 00:07:59.070 ⇒ 00:08:06.759 Hannah Wang: Yeah, so I just want Cursor to have access to Robert’s LinkedIn profile. Like, that’s all I want, like…
53 00:08:06.760 ⇒ 00:08:23.759 Hannah Wang: whether it be his messages in the future, if Robert’s solution doesn’t work, but for right now, like, I guess this main feed right here, his home feed, just scraping it and telling me, like, oh, these are the events that people are going to or hosting.
54 00:08:24.650 ⇒ 00:08:25.140 Brylle Girang: Okay.
55 00:08:25.140 ⇒ 00:08:26.160 Hannah Wang: Gotcha.
56 00:08:26.160 ⇒ 00:08:45.029 Brylle Girang: Okay, well, if we’re just talking about, like, the technical part of it, we do have lots of options. I’m looking at the MCP server from GitHub right now, that’s the Cardaniel one, number 2, and it looks like it will work, as well as the other APIs that we have. I also know of, like.
57 00:08:45.470 ⇒ 00:08:49.650 Brylle Girang: A scraper platform that is free.
58 00:08:50.430 ⇒ 00:08:57.390 Brylle Girang: You can check this out, where we can get an API key, then it will… we can use cursor to do the scraping for us.
59 00:08:57.890 ⇒ 00:09:03.379 Brylle Girang: My only problem here, and I think this is going to be a big, big problem, is…
60 00:09:03.650 ⇒ 00:09:07.659 Brylle Girang: I know that LinkedIn doesn’t really…
61 00:09:07.890 ⇒ 00:09:11.039 Brylle Girang: Treat scrapers in a good way.
62 00:09:11.040 ⇒ 00:09:11.400 Hannah Wang: Yeah.
63 00:09:11.640 ⇒ 00:09:15.919 Brylle Girang: I guess cursor emphasized that in… in…
64 00:09:16.310 ⇒ 00:09:22.489 Brylle Girang: in number 3 or number 2, I don’t remember. The TOS, specifically.
65 00:09:23.250 ⇒ 00:09:29.700 Brylle Girang: says that’s scraping. Number two, rather. The TOS specifically phrases that scraping.
66 00:09:30.760 ⇒ 00:09:35.490 Brylle Girang: is going to be really, really bad, so… Well.
67 00:09:35.490 ⇒ 00:09:37.879 Hannah Wang: Probably against LinkedIn’s policy.
68 00:09:37.880 ⇒ 00:09:45.260 Brylle Girang: Exactly, exactly. So while… while I can help you out with, like, connecting everyone, I want to make sure that we’re not…
69 00:09:45.260 ⇒ 00:09:59.329 Brylle Girang: going to be in a bad place here. So what I can do is I’m going to connect with the platform team. I think I have enough context, and I think I can translate it to whatever they need. I can connect with them, just to make sure that, you know, we have
70 00:09:59.370 ⇒ 00:10:02.529 Brylle Girang: Second set of eyes here before we do anything.
71 00:10:02.530 ⇒ 00:10:07.129 Hannah Wang: Yeah, I agree. I just don’t want to violate any policies.
72 00:10:07.130 ⇒ 00:10:08.940 Brylle Girang: Yeah, our Robert might get banned.
73 00:10:09.070 ⇒ 00:10:11.820 Hannah Wang: Yeah, I don’t want him to…
74 00:10:12.040 ⇒ 00:10:27.570 Hannah Wang: to get banned. So, yeah, that was just, like, my main… like, I think Robert was pushing, like, oh, try to connect it to LinkedIn, and I think maybe there’s just more nuances, to that connection, so… yeah, if you just…
75 00:10:28.060 ⇒ 00:10:37.680 Hannah Wang: just let me know, like, what the platform team says, and then I… I think I said I’m out of office until…
76 00:10:37.840 ⇒ 00:10:46.969 Hannah Wang: Next Thursday, yeah, so, I think just… you can just send me a bunch of Slack messages on updates, and then I’ll review them once I get back.
77 00:10:47.070 ⇒ 00:10:48.970 Hannah Wang: But,
78 00:10:49.120 ⇒ 00:11:02.890 Hannah Wang: Yeah, thanks for helping me, like, push this. I can obviously do all the research, but I just wanted to connect with the AI or platform team to help push things along.
79 00:11:03.560 ⇒ 00:11:06.139 Brylle Girang: Definitely. Okay, thank you, thank you, Hannah.
80 00:11:06.470 ⇒ 00:11:12.699 Hannah Wang: Yeah, thank you for taking the time. I know it’s, like, an odd time for you, so I appreciate you hopping on.
81 00:11:12.700 ⇒ 00:11:17.199 Brylle Girang: Oh, it’s okay, like, my work hours here are all, all odd, so…
82 00:11:17.200 ⇒ 00:11:22.129 Hannah Wang: I hope you still get enough rest and sleep,
83 00:11:22.280 ⇒ 00:11:27.730 Hannah Wang: Thank you. Even though you work weird hours. But yeah, appreciate you, and talk to you later.
84 00:11:27.730 ⇒ 00:11:32.280 Brylle Girang: Yeah, and have a good rest during your off hours.
85 00:11:32.280 ⇒ 00:11:33.350 Hannah Wang: Thank you. Bye.
86 00:11:33.350 ⇒ 00:11:33.930 Brylle Girang: Bye-bye.