Ceramic
Ceramic Search provides lexical web search for LLMs and AI agents, returning relevant public web content for keyword queries.
Verdict
Common use cases
- Verify product claims with live sources
- Compare competitor pricing and features
- Find recent news on industry topics
- Research regulatory changes affecting clients
- Gather customer reviews from multiple sites
Integration
- Vendor
- Ceramic
- Category
- other
- Auth
- API_KEY
- Tools
- 1
- Composio slug
ceramic
Tools
- Search Web
Search the public web with concise lexical keywords and return up to 10 relevant pages with descriptions. Ceramic matches keywords rather than semantic intent, and every call consumes credits, so use one focused query instead of redundant p
Setup
Setup guide
- 1Open your Switchy workspace and navigate to Settings, then Integrations. Click Add Integration and select Ceramic from the list. You'll need an API key from your Ceramic dashboard — log into Ceramic, go to API Settings, and generate a new key with search permissions. Paste the key into Switchy and click Connect. Switchy will verify the key has valid credits remaining. To test, create or open a Project and type '@Ceramic search web: artificial intelligence news'. The AI will invoke Ceramic's search tool and return a list of pages. If you see results with titles and descriptions, the connection works. Remember that each search deducts credits, so the AI should use targeted keywords rather than broad queries.
What teammates see: by default, memories from Ceramic are scoped to the Project (PROJECT visibility) - you can mark any memory PRIVATE or share it ORG-wide.
Works well with
Top models
Compatibility data appears once enough Projects have used this MCP together with a given model.
How Switchy teams use it
Starter prompts
Competitor Feature Audit
@Ceramic search web: [competitor name] product features pricing. Return the top results with descriptions, then summarize what features they emphasize that we don't currently offer.
Regulatory Update Check
@Ceramic search web: [regulation name] 2025 changes requirements. List the pages found, then highlight any new compliance obligations mentioned in the descriptions.
Customer Sentiment Scan
@Ceramic search web: [product name] review complaints issues. Show me the results, then summarize common pain points customers mention across these sources.
Industry News Digest
@Ceramic search web: [industry topic] news January 2025. Return the top articles with descriptions, then write a three-paragraph summary of the major trends or events.
Vendor Evaluation Research
@Ceramic search web: [vendor name] case studies customer success. List the pages you find, then extract key claims about their track record and client outcomes.
Example outputs
Illustrative - representative of the model's voice and quality, not literal recordings.
@Ceramic search for recent SEC filings on renewable energy tax credits
Ceramic returned 10 pages matching "SEC filings renewable energy tax credits", including links to Form 10-K excerpts from three solar manufacturers, two IRS guidance documents, and a law firm memo on ITC eligibility. Each result includes a 2-sentence description. This illustrative example shows how Ceramic surfaces public documents via lexical keyword matching rather than semantic search—results depend on exact phrasing and may include tangential matches if keywords appear in unrelated contexts.
Ceramic uses lexical (exact keyword) matching, not semantic understanding, so prompt phrasing matters. Every search consumes account credits. Best for finding specific documents or terms of art where you know the exact language used in the source material. Requires API_KEY auth with sufficient credit balance.
@Ceramic find public GitHub issues mentioning "CORS preflight failure" in the last 30 days
Ceramic returned 8 GitHub issue pages containing the exact phrase "CORS preflight failure", spanning repositories for three web frameworks and two API gateway projects. Descriptions highlight whether the issue is open or closed and include the repository name. This illustrative example demonstrates Ceramic's ability to surface recent technical discussions, though results are limited to pages where the exact phrase appears—paraphrased issues ("preflight CORS error") won't match unless you adjust keywords.
Lexical search means you must anticipate the exact wording developers use. Ceramic doesn't infer synonyms or related terms. Useful for tracking known error messages or specific jargon across public repos. Each query deducts credits, so refine keywords before searching to avoid multiple attempts.
@Ceramic search for "GDPR Article 17 right to erasure" case law, then summarize the top 3 results by jurisdiction
Ceramic returned 10 pages including two CJEU rulings, three national court decisions (Germany, France, Spain), and four legal commentary articles. The AI then synthesized the top 3 into a jurisdiction-grouped summary: CJEU established the balancing test for public interest vs. erasure rights; German courts applied strict interpretation for search engine delisting; French courts carved exceptions for journalistic archives. This illustrative example shows how Ceramic's lexical retrieval pairs with the AI's reasoning to distill legal research into actionable insights.
This example combines Ceramic's search with the AI's summarization. Ceramic itself only returns raw page links and descriptions—synthesis happens in the AI layer. Lexical matching works well for legal research where statutory language is standardized. Credit cost applies per search, not per result, so one query supports multi-step analysis.
Use-case deep-dives
Ceramic's sweet spot for low-frequency trend checks
A 2-person marketing team at a fintech startup runs a Friday ritual: search for 5 industry keywords to spot emerging trends before writing next week's content. Ceramic fits this use case because the searches are infrequent (5 queries once a week), the keywords are precise ("embedded finance regulation", "API banking adoption"), and the 10-result cap is a feature—it forces the team to review a manageable set instead of 50 tabs. The credit model works in their favor: 20 searches a month is cheap, and lexical matching surfaces exactly what they need without semantic drift pulling in adjacent topics. The boundary: if your trend monitoring expands to daily checks or you need to explore fuzzy concepts ("what are people saying about our space?"), Ceramic's per-call cost and keyword rigidity become friction. But for disciplined, low-volume keyword tracking where you know the terms that matter, this MCP delivers signal without noise. Best for teams that treat search as a scheduled ritual, not an always-on research mode.
Frequently asked
What does the Ceramic MCP do in Switchy?
It lets your AI agents search the public web using keyword-based queries and retrieve up to 10 relevant pages with descriptions per search. Unlike semantic search tools, Ceramic uses lexical matching—you provide concise keywords, and it returns pages that contain those exact terms. Each search call consumes credits from your Ceramic account, so agents should use it sparingly for fact-checking or research tasks that require current web data.
Do I need a Ceramic account to use this MCP?
Yes. You need a Ceramic API key, which means signing up for a Ceramic account and purchasing credits. The MCP authenticates with that key, and every web search your agents run deducts from your Ceramic credit balance. If you're evaluating Ceramic, check their pricing page first—credit costs add up quickly if agents search frequently or your team runs multiple workflows.
Can Ceramic MCP search private or paywalled content?
No. Ceramic only searches the public web—pages that are openly indexed and accessible without authentication. It won't retrieve content behind paywalls, login walls, or private intranets. If your agents need to pull data from internal knowledge bases or subscription services, you'll need a different MCP that integrates directly with those platforms, not a general web search tool.
How does Ceramic compare to just using Google Search API?
Ceramic is simpler and cheaper for low-volume keyword searches, but less flexible. Google Search API offers richer metadata, more advanced operators, and better ranking signals, but requires OAuth setup and costs more per query. If your agents need basic web lookups a few times per day, Ceramic works fine. For high-frequency research or nuanced queries, Google's API is worth the extra complexity.
Who on the team should connect the Ceramic MCP?
Whoever manages your team's API integrations and budget. That person needs to create the Ceramic account, buy credits, generate the API key, and paste it into Switchy. Since every agent search consumes credits, they should also monitor usage in Ceramic's dashboard to avoid surprise bills. If multiple people build workflows, make sure one owner tracks credit burn across the team.