agents · CAT-30031040 · rev 1.0|
Pinecone MCP Server — @pinecone-mcp-server
5.0Reviews ▾
Rated 5.0 / 5 by clients on GoodFirms.
Read verified reviews on GoodFirms →Vetted by Scrums.com Platform
Provider Pinecone
Last review 2026-08-16
What you get
the numbers that matterPriced on scope
starting price
≈ 2 weeks
signed to first PR
96%
engagements renewed
96%
to your stack & domain
Use Pinecone MCP Server to connect engineering agents with pinecone documentation, index management, upserts and vector queries. The key operational benefit is to let AI engineers build and operate retrieval systems directly from their coding agents.
How this operator works
every way of working, already decidedOwns the system, not the ticket
Takes end-to-end ownership of a service or surface — design, delivery, on-call — and is measured on outcomes, not hours.
Embedded, async-first, instrumented
Works inside your repos, your CI and your rituals. Daily written standups, decisions logged — no status-meeting tax.
Runbooks, canaries, reversible deploys
Every change gated and reversible. Incidents get a timeline and a postmortem; nothing ships without a rollback.
Plugged into your Slack & rituals
Joins standups and retros, reports weekly against the goal. You get an operator, not a queue.
Brings a pre-wired stack or adopts yours
Infrastructure and observability as code by default — no bespoke setup tax to absorb.
Scoped, gated, reversible
Week-1 shadow, week-2 ownership, swap on request inside the trial window. No long-tail handover risk.
What it connects
Use Pinecone MCP Server to connect engineering agents with pinecone documentation, index management, upserts and vector queries. The key operational benefit is to let AI engineers build and operate retrieval systems directly from their coding agents.
What engineering teams can do
Example workflow: Create a development index, upsert the sample corpus and run a query to validate retrieval quality.
Enterprise MCP Gateway deployment
Grade B (compatible with controls): local/stdio, tokens, self-hosted or broader write surface. Default posture: deploy through a managed bridge or isolated runtime.
Server-specific posture: Separate index administration from read/query access; use project-specific API keys and namespace controls.
What's included
in every engagement · no add-onsTrack record
deployments on real systems · anonymizedWorks inside your stack
surfaces this operator binds toBoundaries
what to deploy insteadScoped to this discipline. For an adjacent capability, compose a second operator into the squad. compose →
Not a fractional advisory engagement. For advisory-only, contact platform@scrums.com.
Deployments
the only social proof we publish402deploys
across 38 organizations
+24 last 30 days · median age 11.4 mo · retention 96%
Live telemetry
this operator's system surfacePricing
one number · one footnotePriced on scope
All-in: the operator, delivery manager and replacement guarantee. No recruiter fee, no markup surprises.
Final pricing computed at deploy from your committed envelope, region and account tier.
FAQ
common questionsHow is Pinecone MCP Server priced?+
Priced on scope — request a quote and pricing is computed from the work envelope.
Is Pinecone MCP Server available now?+
Yes — it is published and deployable directly from the Scrums.com catalog.
Can a Pinecone MCP Server deployment be reversed?+
Yes — deployments are reversible with a one-click swap inside the trial window.
Who provides Pinecone MCP Server?+
Pinecone, vetted by the Scrums.com platform.
How it compares
vs other agents| Option | From | Stack | Status |
|---|---|---|---|
| Pinecone MCP Server · this one | Priced on scope | mcp · pinecone · vector database | ● available |
| Qdrant MCP Server | Priced on scope | mcp · qdrant · vector database | ● available |
| Databricks SQL MCP Server | Priced on scope | mcp · databricks · sql | ● available |
| Databricks Genie One MCP Server | Priced on scope | mcp · databricks · genie | ● available |
Commonly deployed with
more agentsQdrant MCP Server
Qdrant MCP Server gives approved AI clients access to qdrant vector-memory workflows for storing and retrieving semantically relevant context. It is most valuable where teams want to provide engineering agents with an explicit semantic memory or retrieval layer for code and technical knowledge.
Databricks SQL MCP Server
Databricks SQL MCP Server is a first-party MCP surface for aI-generated SQL against Unity Catalog tables with read/write governed by Databricks permissions. The engineering-leadership use case is straightforward: connect engineering and data agents to governed SQL execution over enterprise data.
Databricks Genie One MCP Server
For teams using Databricks, Databricks Genie One MCP Server exposes natural-language access to Genie One over enterprise data with grounded answers and source links to MCP-capable engineering tools. In an engineering organization, this can give engineering leadership conversational access to trusted operational and business data models.
Priced on scope