@tessera-llm/mastra
Advanced tools
Drop-in Tessera integration for the Mastra agent framework. One line of config routes every Mastra Agent's LLM calls through Tessera's auto-route + auto-cache + auto-compress + auto-batch proxy. Compatible with @ai-sdk/openai, @ai-sdk/anthropic, @ai-sdk/m
@tessera-llm/mastraDrop-in cost optimization for the Mastra agent framework. One line of config routes every Mastra Agent's LLM calls through the Tessera optimization proxy: auto-route to cheaper-equivalent models, exact + provider-prompt-cache hits, prompt compression with per-stack quality canary, batch arbitrage on async-tolerant calls. Free Sandbox tier: 60M tokens/month, no card. Production: 20% of measured savings, $0 if we save you nothing.
Companion to tessera-sdk (vanilla provider SDKs), tessera-langchain (LangChain integration), tessera-vercel-ai (Vercel AI SDK integration), tessera-llamaindex (LlamaIndex integration), tessera-pydantic-ai (Pydantic AI integration), tessera-crewai (CrewAI multi-agent integration), and tessera-autogen (AutoGen 0.4+ multi-agent integration). Same proxy, same mechanic stack, Mastra-shaped API.
import { Agent } from "@mastra/core/agent";
import { createOpenAI } from "@ai-sdk/openai";
import { tesseraOpenAIConfig } from "@tessera-llm/mastra";
const openai = createOpenAI({
apiKey: process.env.OPENAI_API_KEY!,
...tesseraOpenAIConfig({ apiKey: process.env.TESSERA_API_KEY! }),
});
export const supportAgent = new Agent({
name: "Support",
instructions: "Triage incoming support tickets in two sentences.",
model: openai("gpt-4o"),
});
Three changes in your code: one import, three lines in the constructor call. Every agent.generate() and agent.stream() call lands on the Tessera proxy with auto-route + auto-cache + auto-compress + auto-batch applied.
Or use the convenience factory (skips the explicit createOpenAI import):
import { Agent } from "@mastra/core/agent";
import { tesseraOpenAI } from "@tessera-llm/mastra";
const openai = await tesseraOpenAI({
openaiApiKey: process.env.OPENAI_API_KEY!,
tesseraApiKey: process.env.TESSERA_API_KEY!,
});
export const supportAgent = new Agent({
name: "Support",
instructions: "Triage incoming support tickets in two sentences.",
model: openai("gpt-4o"),
});
Mastra's model router accepts AI SDK provider modules natively, so any provider returned by Tessera's factory works as a drop-in for the model: field on new Agent({...}).
npm install @tessera-llm/mastra @mastra/core
# Plus whichever provider package you use:
npm install @ai-sdk/openai # or @ai-sdk/anthropic / @ai-sdk/mistral / @ai-sdk/groq / @ai-sdk/cohere
The @ai-sdk/* and @mastra/core packages are peer dependencies. Install only the providers you actually use. The Mastra core SDK is whatever version you already have on the project.
Get a free Tessera API key (60M tokens/mo, no card) at tesseraai.io/dev. Sign-up takes ~30 seconds and returns an instant tk_… key plus magic-link dashboard access.
| Provider | @ai-sdk package | Tessera config function | Convenience factory |
|---|---|---|---|
| OpenAI | @ai-sdk/openai | tesseraOpenAIConfig | tesseraOpenAI |
| Anthropic | @ai-sdk/anthropic | tesseraAnthropicConfig | tesseraAnthropic |
| Mistral | @ai-sdk/mistral | tesseraMistralConfig | tesseraMistral |
| Groq | @ai-sdk/groq | tesseraGroqConfig | tesseraGroq |
| Cohere | @ai-sdk/cohere | tesseraCohereConfig | tesseraCohere |
Generic dispatcher available too: tesseraConfig("openai", { apiKey: "tk_..." }) returns the right { baseURL, headers } object regardless of provider. Useful when the provider is parameterized at runtime.
Real customer-support agent on gpt-4o, 5B tokens/month, OpenAI list prices:
| Stage | Cost / mo | Saved |
|---|---|---|
| Baseline (OpenAI direct via Mastra) | $24,000 | n/a |
| + Tessera (route, cache, prompt-cache headers, compress, M9 ceiling, batch) | $9,400 | $14,600 |
| Tessera fee (20% × savings) | $2,920 | n/a |
| You net pay | $12,320 | $11,680 / mo saved |
Verify the savings math yourself. Every billable line traces back to two immutable cost figures pinned to a multi-source pricing catalog snapshot captured at request time. Two engineers, three hours, can re-derive any month from raw inputs. Full procedure at tesseraai.io/trust.
Quality canary across the full mechanic stack: mean-score 0.96 (floor 0.95). 0.95 SLA held all 30 days. Full breakdown: worked example with mechanic-level numbers + canary results.
Same mechanic stack as the main tessera-sdk. Each mechanic is opt-in per workload, observable per request, and bypasses when its quality canary drops below the per-stack 0.95 floor.
| Mechanic | What it does | Typical savings |
|---|---|---|
| Auto-route (m1) | Route to a cheaper-equivalent model gated by a daily promptfoo canary on your eval set | 15–35% on routed calls |
| Auto-cache (m2) | sha256 cache on the canonical request body, 7-day TTL, Cloudflare edge KV | 5–40% depending on prompt repetition |
| Auto-compress (m3) | Per-role heuristic compression (system + user toggles independent). Preserves code fences and JSON shapes. | 5–15% on prompt tokens |
| Prompt cache (m6) | Inject provider-native cache headers: OpenAI cached-input (50% off), Anthropic cache_control: ephemeral (90% off cache reads) | 50–90% on cached prefixes |
| Context prune (m7) | Conservative trim on long conversations (system + last 8 turns; TF-IDF rerank on RAG attachments) | 5–25% on multi-turn workloads |
| Output-length ceiling (m9) | Daily compute fits p90 of completion length per workload, injects maxTokens = p90 × 1.3 | 5–15% on completion cost |
| Batch arbitrage (m10) | Route async-tolerant Agent calls to provider Batch APIs (OpenAI Batch + Anthropic Message Batches both 50% off) | 50% on batch-eligible traffic |
| Cross-provider failover (m11) | When primary upstream returns 5xx / connection error / timeout, retry on OpenRouter (opt-in, default OFF) | Reliability primitive, n/a cost |
| Per-provider circuit breaker | Rolling 5xx-rate state machine per upstream. When a provider degrades, auto-route skips its intra-provider alternative mappings until the half-open probe succeeds. | n/a (keeps the savings stack honest) |
Existing customers of tessera-sdk, tessera-langchain, tessera-llamaindex, or tessera-vercel-ai keep their rate_locked_pct (if any) on this package too. Same tk_… key, same billing record.
Same proxy. Same mechanics. Same billing. The five packages target different code surfaces:
tessera-sdk: patches the underlying provider client constructors (OpenAI, Anthropic, etc.) directly via tessera.activate(key). Use when calling provider SDKs without a framework.tessera-langchain: wires into LangChain ChatModel constructors. Use when you're on LangChain.tessera-llamaindex: wires into LlamaIndex LLM adapter constructors. Use when you're on LlamaIndex.tessera-vercel-ai: wires into the Vercel AI SDK provider factories. Use when you're on ai core + @ai-sdk/* without Mastra.tessera-mastra (this package): same Vercel AI SDK provider factory shape, Mastra-shaped README and E2E gate. Use when you're on Mastra Agents.Pick whichever fits your codebase. Side-by-side install is supported: all five resolve to the same proxy and same billing record.
No. The Vercel AI SDK provider object that Mastra accepts is unchanged in shape (agent.generate(), agent.stream(), generateObject, schema-constrained tool calls, and RAG retrieval workflows all work unchanged). Auto-route gates on tool-calling capability so an agent using tools never gets routed to a non-tool-capable model.
"openai/gpt-4o")?Not directly. Mastra's string shorthand uses environment variables like OPENAI_API_KEY against the provider's canonical endpoint. Tessera needs a custom baseURL + custom x-tessera-api-key header, which the string shorthand doesn't surface. Use the AI SDK provider factory form (shown in the examples above); Mastra accepts it as a first-class alternative to the string shorthand.
Your Agent gets HTTP errors instead of LLM responses. On the proxy side, a per-provider circuit breaker tracks rolling 5xx rates and skips degraded providers in auto-route decisions. Cross-provider failover (m11) is opt-in and re-routes to OpenRouter when the primary upstream is down. See the workload toggle in the dashboard.
They pass through. Tessera does not aggregate quotas across customers. Your provider rate limits apply normally; the proxy enforces only the Tessera tier limits (30 rpm Free Sandbox, 60 rpm Production by default; higher on request).
No. We log only token counts, cost deltas, mechanics_stack, and provider response status. Prompts and completions are never persisted. Full data handling on tesseraai.io/security.
tesseraOpenAIConfig vs tesseraOpenAI)?The config function returns the kwargs object you spread into createOpenAI(...): explicit, easy to combine with other settings (organization, custom fetch, etc.). The convenience factory imports createOpenAI for you and pre-merges. Use whichever you find more readable. Both ship in the same package.
Tessera is the substrate layer for LLM cost optimization, also called the Optimize Layer in our product surface. A thin proxy that sits in your application's request-path, applies a conservative cascade of optimization mechanics, and measures every saved dollar against an audit-immutable baseline. We bill 20% of verified savings, prepaid. Zero savings = zero fee. No per-token gateway fee, no subscription, no minimum monthly commitment; the category we operate in is "success-fee LLM optimizer," distinct from per-token AI gateways and observability dashboards.
Where observability tools tell you what you spent and AI gateways re-shape the request without measuring the cost delta, Tessera is the layer that does both, and only takes a cut when the measured savings are positive. The verified-savings ledger at ledger.tesseraai.io shows every original-vs-actual cost pair, snapshot-pinned to a pricing_catalog version captured at request time. Mid-contract price changes don't retroactively alter past savings. This is the FinOps-friendly model for AI inference: every line of the bill traces to a code-enforced rule.
Apache-2.0. Operated by Fintechagency OÜ (Tallinn, Estonia, registry code 16638667). Issues: github.com/tessera-llm/tessera-mastra/issues.
FAQs
Drop-in Tessera integration for the Mastra agent framework. One line of config routes every Mastra Agent's LLM calls through Tessera's auto-route + auto-cache + auto-compress + auto-batch proxy. Compatible with @ai-sdk/openai, @ai-sdk/anthropic, @ai-sdk/m
The npm package @tessera-llm/mastra receives a total of 196 weekly downloads. As such, @tessera-llm/mastra popularity was classified as not popular.
We found that @tessera-llm/mastra demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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