Customer research on Reddit with an AI agent: pull full comment threads through MCP

If you have ever tried to answer "what do people complain about in our category?" by reading Reddit, you know the useful part is rarely the post. It is the comment thread underneath, three or four levels deep, where someone explains why they returned the product and five people reply with what they bought instead. This post walks through how to get those threads into an AI agent as structured data, using MCP for chat clients and a plain REST API for scripts.

I work on ProLevelMax, the data source used in the examples below. The approach (discover a source, check the price, run it, page through results) is the part worth taking away.

Getting one thread is easy. Getting a few hundred threads reliably is where the time goes:

What I wanted instead: the agent asks for "comments on this post", gets a price before anything runs, and receives clean records it can count and quote.

ProLevelMax exposes the same data three ways:

For Claude Code, the setup line from SKILL.md is:

claude mcp add --scope user --transport http prolevelmax https://prolevelmax.com/mcp --header "Authorization: Bearer sk_procli_..." Enter fullscreen mode Exit fullscreen mode Once connected, the agent has eight tools. The four that matter for research are procli_discover, procli_inspect, procli_run and procli_runs_get. The REST endpoints mirror them, so I will use REST for the rest of this post because it is easier to show.

1. Discover. You describe what you want in plain words (English or Chinese) and get candidate sources back.

curl https://prolevelmax.com/v1/discover \ -H "Authorization: Bearer sk_procli_..." \ -H "Content-Type: application/json" \ -d '{"query":"reddit comments"}' Enter fullscreen mode Exit fullscreen mode The response has recommended and items. Each source carries a scraper id, a title, bestFor, a verdict ( recommended, ok or not_recommended ), a why, its pricing and an estimate. For Reddit there are separate sources for search, subreddit feeds, a post with its comments, post comments page by page, and replies under one comment for deep threads.

2. Inspect. Before running anything, ask for the input fields and a quote.

curl https://prolevelmax.com/v1/inspect \ -H "Authorization: Bearer sk_procli_..." \ -H "Content-Type: application/json" \ -d '{"scraper":"procli_reddit_b","input":{"post_id":"t3_1abcde"}}' Enter fullscreen mode Exit fullscreen mode The response shape (values omitted):

{ "scraper": "procli_reddit_b", "inputFields": [ { "name": <string>, "type": <string>, "required": <bool>, "description": <string>, "paging": <bool> } ], "exampleInput": {... }, "pagingNote": <string>, "quote": { "maxCharge": <number, USD>, "maxChargeDisplay": <string>, "needsConfirmation": <bool>, "balanceTooLow": <bool> } } Enter fullscreen mode Exit fullscreen mode quote.maxCharge is the most this run can cost. needsConfirmation is true when the quote is above $0.10. Fields marked paging: true are the ones you fill from the previous result to get the next page.

curl https://prolevelmax.com/v1/run \ -H "Authorization: Bearer sk_procli_..." \ -H "Content-Type: application/json" \ -d '{"scraper":"procli_reddit_b","input":{"post_id":"t3_1abcde"}}' Enter fullscreen mode Exit fullscreen mode A finished run returns runId, items, count, a page object with cursor values for the next page, cost (with amountDisplay ), quote, wallet (with balanceDisplay ) and download links for json, csv and xlsx. For long jobs, send "async": true and you get a 202 with a runId to poll at GET /v1/runs/:id.

4. Download. GET /v1/runs/RUN_ID/download?format=csv (or xlsx, json ). Nested fields become a.b columns in CSV.

This pulls every page of comments for one Reddit post, refuses to run anything that needs confirmation, and writes the records to a JSON file. Replace the key and the post id.

import json, sys, requests API = " https://prolevelmax.com/v1 " H = { " Authorization ": " Bearer sk_procli_... " } SOURCE = " procli_reddit_b " # "Post comments", page by page inp = { " post_id ": " t3_1abcde " } # the post you want comments, spent = [], [] for _ in range ( 10 ): # hard stop at 10 pages info = requests. post ( f " { API } /inspect ", headers = H, json = { " scraper ": SOURCE, " input ": inp }). json () if info [ " quote " ][ " needsConfirmation " ]: sys. exit ( f " Quote is { info [ ' quote ' ][ ' maxChargeDisplay ' ] }, stopping for review " ) run = requests. post ( f " { API } /run ", headers = H, json = { " scraper ": SOURCE, " input ": inp }). json () comments += run [ " items " ] spent. append ( run [ " cost " ][ " amountDisplay " ]) paging = [ f [ " name " ] for f in info [ " inputFields " ] if f. get ( " paging " )] page = run. get ( " page " ) or {} if not paging or not any ( page. get ( n ) for n in paging ): break # no next cursor: done inp. update ({ n: page [ n ] for n in paging if page. get ( n )}) json. dump ( comments, open ( " comments.json ", " w " ), ensure_ascii = False, indent = 2 ) print ( len ( comments ), " comments, charges: ", spent, " balance: ", run [ " wallet " ][ " balanceDisplay " ]) Enter fullscreen mode Exit fullscreen mode The script does not hard-code the cursor field name. It reads which input fields are marked paging from inspect and copies matching values from the result's page object, which is how the docs describe paging for per-call sources.

Error handling is left out to keep it short; errors come back as JSON with a stable type (for example insufficient_balance, spend_limit, invalid_input, rate_limited ) you can branch on.

From here, feed comments.json to whatever model you use and ask for themes with counts and verbatim quotes. Asking for quotes with links keeps the summary honest, because you can check each claim against the thread.

Running an agent against a paid API is only comfortable if spend has a ceiling. The pieces that give you one:

Billing is pay per use: some sources charge per call, others per result plus a per-run fee with a minimum. Most Reddit sources are per call. Current rates are on the pricing page, and new accounts get $1 of credit after email verification, which is enough to try the flow above.

If something in the flow is unclear or broken, email toph@prolevelmax.com.