genai-solutions-mcp
This server lets an AI assistant query a curated, offline snapshot of 1,212 generative AI tools.
Search tools by free text and filters: type, ecosystem, origin, capabilities, and curator picks.
Retrieve full details for any tool by ID.
List all categories with record counts to build valid filters.
Compare 2–4 tools side by side on the same fields.
Runs without API keys, network access, or a database—data ships with the repo.
Click on "Deploy Server".
Wait a few minutes for the server to deploy. Once ready, it will show a "Started" state.
In the chat, type
@followed by the MCP server name and your instructions, e.g., "@genai-solutions-mcp Find open-source video editing tools that run locally"
That's it! The server will respond to your query, and you can continue using it as needed.
Here is a step-by-step guide with screenshots.
genai-solutions-mcp
An MCP server that exposes a curated database of generative AI tools — 1,212 records I have maintained in Notion since May 2024 — as four tools an AI assistant can query directly.
Instead of asking a model what AI tools exist and getting a plausible but stale answer, you ask it to search a dataset that has a person behind it.
> Which open-source tools in here run locally and have a CLI?
> Compare Firecrawl and the other scraping options.Install
npm install
npm run build
npm startNo API key, no network, no database. The dataset ships with the repo.
Register it with an MCP client (Claude Desktop shown here):
{
"mcpServers": {
"genai-solutions": {
"command": "node",
"args": ["/absolute/path/to/genai-solutions-mcp/dist/src/index.js"]
}
}
}Related MCP server: disvr
Tools
Tool | Purpose |
| Free-text + filters (type, ecosystem, capabilities, origin, picks) |
| Full record for one id |
| Every category with its record count |
| 2–4 records aligned on the same fields |
Design decisions
A committed snapshot, not a live Notion proxy. The obvious design is to
call the Notion API on every tool call. It is also the one that makes the
repo useless to everyone but me: you would need my token and my database.
Instead, scripts/sync-notion.ts exports Notion to data/solutions.json,
which is versioned here, and the server only reads that file. The trade-off
is freshness — the data is as current as the last sync — against a server
that anyone can clone and run in fifteen seconds, with no credentials, no
network dependency at call time, and no rate limit. The underlying data
changes weekly at most, so freshness is the cheaper thing to give up.
Substring search, not embeddings. 1,212 records is a sub-millisecond linear scan. A vector index would add an embedding step to the sync, a model dependency, non-deterministic results, and an index to keep consistent with the snapshot — in exchange for semantic recall on a corpus where the useful queries are mostly names and categories. If the dataset grows an order of magnitude or the summaries get longer, this is the first thing to revisit.
Search returns a projection, not full records. search_solutions returns
only id, name, type and url. Returning complete records for a 20-result
query would spend a large amount of the agent's context on fields it usually
does not need; get_solution is there for when it does.
A property whitelist in the sync, not a blacklist. The Notion database
contains internal workflow state and attachments that have no business
being public. scripts/sync-notion.ts names the properties it exports, so
adding a private column in Notion later cannot silently leak it here.
Known limitations
Notion's
Typeis a single select, so each tool has exactly one category even when two would fit.Category values were entered by hand over two years and are uneven; the sync folds casing duplicates but does not merge near-synonyms.
No relevance ranking beyond field-weighted substring matching.
Attribute tagging is uneven.
LocalandOpen Sourcewere applied at different periods with different habits, and they overlap on only one record even though many tools qualify for both. Filters are honest about what is tagged, not about what is true — a property this dataset shares with most real internal databases.The corpus starts in May 2024. A dozen records carry an earlier date: those are tools I had found and tested before, backdated by hand when I entered them.
Node resolution depends on the host environment. The server was observed starting under two different Node installations on the same machine depending on the launching context. Pin the runtime path in your client config if that matters to you.
Maintenance
Both scripts are maintainer-only and need Notion credentials.
Sync the snapshot:
NOTION_TOKEN=… NOTION_DATA_SOURCE_ID=… npm run sync
git diff data/solutions.json # read it before committingBackfill missing capture dates. The Date property is the day I
captured a tool, entered by hand, so it is occasionally left empty. This
fills the gaps with the page's creation time, which is the closest
available proxy. It runs as a dry run by default — read the output before
applying.
NOTION_TOKEN=… npx tsx scripts/backfill-dates.ts
NOTION_TOKEN=… npx tsx scripts/backfill-dates.ts --applyLicense
MIT
Available Tools
4 toolscompare_solutionsCompare solutionsB
Return 2 to 4 solutions side by side on the same fields.
Inputs: ids (required).
get_solutionGet one solutionA
Return the full record for a single solution by id.
Inputs: id (required).
list_categoriesList categoriesA
Return every category present in the database with its record count, so filters can be built against real values rather than guesses.
Inputs: no named parameters.
search_solutionsSearch GenAI solutionsA
Search a curated database of generative AI tools by free text and filters. Returns a short projection (id, name, type, url); call get_solution with an id for the full record.
Inputs: type, limit, query, origin, +3 more.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
Loading tool schema changelog…
TDQS
Scored across 4 tools
Each tool has a clearly distinct purpose: search for filtering, get for full details, list categories for filter options, and compare for side-by-side comparison. No overlap exists.
All tool names follow a consistent verb_noun pattern in snake_case (search_solutions, get_solution, list_categories, compare_solutions), making them predictable and easy to understand.
With four tools, the server is well-scoped for a curated database of generative AI solutions. Each tool earns its place, covering search, retrieval, category listing, and comparison without unnecessary bloat.
The tool set covers the core read-only operations needed for a solutions database: discovery (search), detail retrieval (get), filter exploration (list_categories), and comparison. No obvious gaps—the domain is fully addressed.
Maintenance
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