@reachpad/mcp
Official@reachpad/mcp
reachpad ermöglicht Claude, Codex und anderen Coding-Agenten, Full-Stack-Apps in persistenten Workspaces zu entwickeln und per Link zu teilen – ohne separate Bereitstellung. Ein Workspace ist ein Cloud-Entwicklungsrechner, den ein Agent selbst bedient: ein Repository, ein Dateisystem, installierte Abhängigkeiten und Build-Zustand, die alle zwischen Aufrufen überleben – keine ephemere Sandbox, die vergisst. Prozesse sind die Ausnahme; siehe unten.
Dies ist der MCP-Server. Er ermöglicht Claude, ChatGPT, Cursor, OpenCode oder deinem eigenen Agenten, eine Umgebung zu erstellen, Befehle darin auszuführen, sie zu forken und später darauf zurückzukommen – ohne dass ein Entwickler dafür einen Laptop offen halten muss.
Er ist persistent. Pausiere ihn und die Festplatte wird versiegelt; der nächste Aufruf bootet aus diesem Siegel mit Dateien, Installationen und Git-Zustand intakt, statt neu aufzubauen. Prozesse sind die Ausnahme: Ein Start ist immer ein Kaltstart.
Er forkt. Zwanzig Versuche von einem vorbereiteten Zustand kosten jeweils ein Delta, nicht zwanzig Neubauten – denn die Umgebung ist eine Snapshot-Kette, keine Maschine.
Er kann Geheimnisse aus der Box heraushalten. Eine vermittelte Anmeldeinformation wird an der Grenze in deinem Namen aufgerufen, und ihr Wert gelangt nie in die Umgebung, das Protokoll oder den Speicher. Eine Anmeldeinformation, die stattdessen in die Umgebung geschrieben wird, ist dort – wie vorgesehen – lesbar.
Er ist agentenunabhängig. Die REST-API ist kanonisch; dieser Server, das SDK und die CLI sind Übersetzungen davon. Bring deinen eigenen Agenten mit.
Die API ist die Produktgrenze, keine Web-UI: reachpad.dev.
Installation
npx -y @reachpad/mcp # stdio, for a local clientIn Claude Code:
claude mcp add reachpad -e REACHPAD_IDENTITY_CREDENTIAL=… -- npx -y @reachpad/mcpRelated MCP server: Uten Agent Terminal MCP
Zwei Transports, eine Implementierung
npx @reachpad/mcp # stdio
REACHPAD_MCP_HTTP_PORT=8722 npx @reachpad/mcp # streamable httpstdio ist das, womit ein lokaler Client spricht; Streamable HTTP ist das, womit ein Remote-Connector spricht. Gleiche Tools, gleiches Verhalten – hinzugefügt statt abgespalten, denn zwei Implementierungen einer Oberfläche sind der Weg, auf dem sie auseinanderdriften.
Die HTTP-Seite antwortet mit 405 auf GET: Jedes Tool hier ist Request/Response, und die Spezifikation erlaubt es, den serverinitiierten Stream abzulehnen, statt eine Verbindung für Verkehr offen zu halten, der nie kommt. Es gibt keine Sitzungen – nichts wird über Aufrufe hinweg gehalten, das ein Neustart nicht neu aufbauen könnte. Und sie trägt keine eigene Anmeldeinformation: Was auch immer die HTTP-Anfrage autorisiert, autorisiert reachpad.
Konfiguration
Variable | Bedeutung |
| dein reachpad-Host. Klartext- |
| deine benutzerspezifische Anmeldeinformation. Sie benennt ein Konto und kann für kein anderes handeln – der Server nimmt die Identität aus dem eigenen Datensatz der Anmeldeinformation, nie aus der Anfrage. |
| optional, pro Umgebung begrenzt und widerrufbar. Wenn gesetzt, verwendet |
| HTTP statt stdio bereitstellen. |
| Standard |
| Bearer-Token, in konstanter Zeit verglichen. Fehlt er, ist jeder Aufrufer, der den Port erreichen kann, autorisiert, und der Server sagt das auf stderr. |
| durch Kommas getrennt. Eine Anfrage mit einem nicht gelisteten |
Wenn mehrere Anmeldeinformationen gesetzt sind, gewinnt die engste, und eine abgelehnte Anmeldeinformation wird nie unter einer breiteren erneut versucht – ein Fallback wäre eine Privilegieneskalation, die niemand durchführen wollte.
Tools
Tool | Was es tut |
| verbleibende Rechenguthaben. Ein Guthaben läuft eine Standardumgebung für eine Minute. |
| eine neue Umgebung, optional mit einem Repository, das in |
| deine Umgebungen und wie viele Forks jede hat |
| wovon sie bootet: ihr Kopf-Snapshot, ihre Protokollposition und ihr Fork-Baum |
| ein Befehl, sein Exit-Code und seine Ausgabe. Eine pausierte Umgebung wird fortgesetzt, um ihn zu bedienen. |
| Fork vom letzten versiegelten Snapshot; das Original bleibt unberührt |
| öffne einen Port für das Web und erhalte den Link, der ihn erreicht. Idempotent pro Port. |
| die Ports, die diese Umgebung offen hat, älteste zuerst, mit ihren Links |
| schließe einen Port. Das spätere Wiederöffnen prägt einen anderen Link. |
| archiviere sie und gib den Planslot frei. Nichts wird gelöscht – Snapshots und Verlauf überleben. |
Bewusst nicht hier: das Starten eines Agenten innerhalb der Umgebung. Es steht auf der Roadmap von reachpad und ist noch nicht in der Flotte – ein Tool, das immer fehlschlägt, kostet ein Modell einen Zug und lehrt es, dem Rest zu misstrauen, also bewirbt dieser Server nichts, was er nicht bedienen kann.
Was ein Port-Link ist und was nicht
Lesenswert, bevor du einen an jemanden weitergibst, denn nichts davon ist aus der URL ersichtlich:
Jeder, der bei Reachpad angemeldet ist und den Link hat, kann ihn öffnen. Es ist keine private URL und keine sichere. Behandle ihn wie eine Vorschau-Bereitstellung.
Der Link ist eine Adresse, keine Kopie. Starte die App auf demselben Port neu, und derselbe Link bedient die neue Version.
Ein laufender Prozess überlebt eine Pause nicht. Die Umgebung kaltbootet mit intakten Dateien und nichts Läuft, also antwortet der Link nach einer Pause mit einem Fehler, bis wieder etwas auf diesem Port lauscht. Die Anfrage eines Besuchers weckt eine pausierte Umgebung; sie startet nichts darin neu.
expose_portwählt den Port danach an und sagt dir, ob nichts geantwortet hat, denn ein Link zu einem Port, den nichts bedient, sieht genauso aus wie ein funktionierender Link. Übergibcheck: false, um das zu überspringen – das Anwählen setzt eine pausierte Umgebung fort.Mit nur
REACHPAD_API_KEYmuss der Schlüssel--role ownersein. Eincollaborator-Schlüssel wird abgelehnt: Auflisten gibt Live-Tokens zurück, und ein Token ist eine Fähigkeit.
Die Regeln, nach denen es gebaut ist
Das sind die Arten, wie ein naiver Client einer Streaming-Exec-API ein Modell in die Irre führt, und was dieser stattdessen tut.
Ein nicht abgeschlossener Stream ist UNBEKANNT, nie Erfolg. Wenn die Antwort ohne ein terminales Ereignis endet, sagt das Tool das in genau diesen Worten. Es ist kein Null-Exit, und ein Agent darf einen nicht-idempotenten Befehl nicht aufgrund dessen erneut versuchen.
Seine Frist ist lockerer als die des Servers, sodass eine serverseitige Antwort immer das Rennen gewinnt. Ein Client, der zuerst aufgibt, verwandelt „dein Build ist fertig" in „unbekannt", und die Zahlen werden vom Server gespiegelt statt geraten.
Ablehnungen tragen Abhilfen, keine Codes. An deinem Planlimit erhältst du das Limit, deine aktuelle Anzahl und was zu tun ist – die Zahlen kommen vom Server, denn ein im Client hartcodiertes Limit ist eine Lüge, sobald sich dein Plan ändert.
Ergebnisse sind Handles, keine Nutzlasten. Ausgabe wird mit der genannten Anzahl verworfener Bytes abgeschnitten. Build-Protokolle können Megabytes groß sein, und ein MCP-Ergebnis dieser Größe zerstört den Kontextfenster des Aufrufers.
Eine Ablehnung ist ein Ergebnis, kein Transportfehler, damit das Modell sie lesen und handeln kann. Nur ein unbekanntes Tool ist ein Protokollfehler.
Test
node --test 'test/*.test.mjs'Kein Netzwerk und keine Anmeldeinformationen. Die Protokollsuite startet den ausgelieferten Server als Kindprozess und spricht echtes JSON-RPC über sein stdio gegen eine Stub-Kontrollebene auf einem echten Socket, sodass nichts unter Test ein interner Import ist. Ein Test führt denselben Ablauf gegen ein echtes reachpad aus und überspringt, wenn kein Endpunkt konfiguriert ist.
Repository
Dieses Repository ist die Quelle. Es ist bewusst getrennt vom reachpad-Backend: Dieser Code ist öffentlich, er wird auf npm veröffentlicht, und sein Release-Workflow hält Veröffentlichungsrechte – nichts davon gehört in dasselbe Repository wie die Kontrollebene. Nichts hier kann den Quellcode des Backends lesen, und kein Job im Backend kopiert Dateien hierher.
Zwei Serverkonstanten sind in src/client.js gespiegelt – die Exec-Gnadenfrist und das Standard-Exec-Timeout. Eine gespiegelte Konstante verrottet normalerweise; diese tut es nicht, weil die eigene CI des Backends dieses veröffentlichte Paket abruft und fehlschlägt, wenn sie nicht übereinstimmen. Die Prüfung lebt dort, wo sich die Zahl ändern würde.
Available Tools
7 toolscheckpoint_environmentFork environmentAInspect
Fork an environment from its last sealed snapshot into a new one. The original is untouched. This is how you try several approaches from one prepared state — the fork costs a delta, not a rebuild.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Name for the fork. | |
| environment | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations (readOnlyHint=false, destructiveHint=false) only partially cover behavior; the description adds crucial detail that the original environment is untouched and explains the delta-based cost. This goes beyond the annotations by specifying what is not modified and the resource implication, enhancing transparency.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two succinct sentences: the first states the core action, the second explains the purpose and cost. No redundant phrasing, perfectly front-loaded, and every sentence earns its place. Ideal conciseness.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple tool with 2 params, no output schema, and partial annotations, the description adequately covers functionality, usage context, and non-destructive behavior. It does not mention the return value, but that is not critical given the lack of an output schema and the simplicity of the operation. Overall, complete enough for an agent.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema coverage is 50% (only 'name' has a description). The description does not add extra meaning to the 'environment' parameter beyond the implied source, and 'name' is already described as 'Name for the fork.' Since coverage is moderate, the description adds minimal value beyond what the schema already provides, so a baseline 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
Clearly states the action (fork an environment from its last sealed snapshot into a new one) and differentiates from siblings by emphasizing the 'original is untouched' and the purpose of trying multiple approaches. The verb 'fork' is specific and the resource (environment) is explicit, with a clear scope (last sealed snapshot).
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Provides clear context for use ('try several approaches from one prepared state') and hints at cost advantages ('costs a delta, not a rebuild'), but does not explicitly name alternative tools or state when not to use it. Still, the rationale is sufficiently clear for an agent to decide.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
create_environmentCreate environmentAInspect
Create a persistent development environment: a filesystem and processes that survive between calls. Optionally clone a git repository into it. Returns the environment id used by every other tool.
| Name | Required | Description | Default |
|---|---|---|---|
| ref | No | Optional branch or tag to check out. | |
| name | No | Optional display name. Reachpad generates one when omitted. | |
| repo | No | Optional git URL to clone into /work. Must be reachable without credentials unless the account has a mirror for it. |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds meaningful behavioral context beyond the annotations: persistence across calls, optional git cloning, and the return value. This complements annotations like openWorldHint=true (cloning) and readOnlyHint=false (creation). It does not mention resource/credit implications or failure modes, but covers the core behavioral contract well.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two sentences, front-loaded with the essential function, and no filler. It efficiently communicates persistence, optional cloning, and the return id—every clause earns its place.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
The description covers the essential facts for a creation tool with no output schema: what is created, persistence, optional repo cloning, and the return id. It does not discuss edge cases like clone failures, name conflicts, or costs, but given the moderate complexity and strong schema/annotations, it is sufficiently complete for an agent to invoke correctly.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100%, so all three parameters (ref, name, repo) are already documented structurally. The description's mention of optional repository cloning adds a small layer of meaning, but it does not enrich parameter semantics beyond what the schema provides, matching the baseline of 3.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses a specific verb ('Create') and clearly identifies the resource ('persistent development environment') with defining traits: a filesystem and processes that survive between calls. It also distinguishes from siblings by noting the returned environment id is used by every other tool, making the tool's role as the foundational creation step unambiguous.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool by stating it returns the environment id used by every other tool, establishing it as the prerequisite step. However, it does not explicitly name alternatives or state when not to use it (e.g., prefer run_command for existing environments), so it falls short of a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
delete_environmentArchive environmentADestructiveIdempotentInspect
Archive an environment, freeing the plan slot it holds. Nothing is deleted: its snapshots and history survive, it simply stops counting as live and can no longer be used.
| Name | Required | Description | Default |
|---|---|---|---|
| environment | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description significantly expands on the annotations by explaining what happens: the environment is no longer usable, its plan slot is freed, and its snapshots and history survive. This adds valuable behavioral nuance beyond the destructiveHint=true and idempotentHint=true annotations, and it does not contradict them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences long, front-loaded with the main action, and every clause adds relevant meaning. There is no repetition, filler, or unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple one-parameter tool with no output schema, the description covers the action, consequences, and non-destructive nature of data. However, it lacks guidance on how to specify the environment parameter and does not explicitly contrast it with related tools, leaving small but real gaps in completeness.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The only parameter 'environment' has no schema description and the description gives no detail about what form it should take (name, ID, path, etc.). Since schema description coverage is 0%, the description was expected to compensate, but it only says 'an environment' without specifying how to identify it.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'Archive' and clearly identifies the resource ('an environment') and the key consequence: freeing the plan slot it holds. It also distinguishes itself from the sibling delete/create tools by explicitly clarifying that nothing is deleted, which prevents confusion with the tool's name.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use the tool: when you want an environment to stop counting as live and free its plan slot, while preserving snapshots and history. It does not explicitly name alternatives or state when not to use it, but the context is clear enough for a simple one-parameter archiving operation.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_credit_balanceGet compute-credit balanceARead-onlyIdempotentInspect
Show this account's remaining compute credits. One credit runs one standard environment for one minute; paused environments use no compute credits.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds valuable context beyond annotations: the definition of a credit (one minute per standard environment) and that paused environments don't consume credits. This enriches understanding of the resource being measured without contradicting the annotations.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose and followed by a concise clarification of credit units. Every sentence adds essential information with no waste.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a read-only, zero-parameter tool with rich annotations and no output schema, the description fully covers what the tool does, the resource it references, and the consumption model. This is sufficient for an agent to decide when to call it and what to expect.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool has zero parameters, so the baseline is 4. The description doesn't need to elaborate on parameters but correctly implies that no inputs are required, making it clear the action is a simple balance query.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool's purpose: 'Show this account's remaining compute credits.' It uses a specific verb (show) and resource (compute credits), and the additional detail about credit usage distinguishes it from sibling tools like create_environment and run_command.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool by explaining how credits are consumed, which helps an agent understand that checking balance is relevant when considering environment execution. It doesn't explicitly mention alternatives or exclusions, but since no sibling tool covers credits, the usage context is clear.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
get_environmentInspect environmentARead-onlyIdempotentInspect
What an environment resumes from: its head snapshot, how far its log had got, and its fork tree. Every start is a cold boot from the head snapshot: files survive, running processes do not.
| Name | Required | Description | Default |
|---|---|---|---|
| environment | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the read-only, idempotent, and non-destructive annotations, the description adds valuable behavioral context: running processes do not survive a cold boot while files do. This is exactly the kind of contextual insight that the annotations alone do not provide.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is compact and well-structured: two sentences front-load the core output details and then add the essential cold-boot behavior. Every sentence earns its place without unnecessary restatement.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a single-parameter, read-only inspection tool, the description is largely sufficient: it names the returned concepts and a key behavioral nuance, and the annotations cover safety and idempotency. It does not describe a concrete output format, but no output schema is present.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The schema exposes one undocumented string parameter, 'environment', and schema description coverage is 0%. The description clarifies that the tool operates on an environment's resumption state, but it does not explain how to obtain or format the environment identifier, e.g. whether it is an ID or name from list_environments.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly identifies what the tool returns: an environment's resumption state, including its head snapshot, log progress, and fork tree. This distinguishes it from siblings like list_environments, create_environment, and delete_environment, which perform different lifecycle operations.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
No explicit alternatives are listed, but the description provides clear operational context: every start is a cold boot from the head snapshot, so this tool helps you understand what state an environment will resume with. The absence of explicit when-not-to-use guidance prevents a 5.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
list_environmentsList environmentsARead-onlyIdempotentInspect
List this account's environments, with how many forks each has.
| Name | Required | Description | Default |
|---|---|---|---|
No parameters | |||
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already express readOnly, openWorld, idempotent, and non-destructive behavior. The description adds behavioral context by scoping to the current account and revealing that fork counts are included in the response. This goes beyond the annotations without contradicting them.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
A single sentence that is front-loaded with the verb 'List' and immediately identifies the resource and output. Every word adds value; there is no unnecessary detail.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given that the tool has no parameters, no output schema, and strong annotations, this description fully covers the core invocation and expected result. An agent has enough information to correctly select and call this tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The tool takes zero parameters, so the baseline of 4 is appropriate. The description does not need to define parameter meanings because there are none to clarify.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description uses the specific verb 'List' and states the exact resource ('this account's environments') plus a meaningful differentiator ('with how many forks each has'). This clearly distinguishes it from get_environment, which focuses on a singular environment.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies when to use this tool—when you need an account-level summary of environments and their fork counts—but it does not explicitly say when to prefer this over get_environment or list other alternatives. It provides clear context but no exclusionary guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
run_commandRun a commandADestructiveInspect
Run one command in an environment and get its exit code and output. Not a shell: pass argv as a list, and ask for a shell explicitly with ["/bin/sh","-lc","…"] if you want one. A paused environment resumes to serve this.
| Name | Required | Description | Default |
|---|---|---|---|
| cwd | No | ||
| env | No | ||
| argv | Yes | ||
| timeout_ms | No | Give up after this long. PASS IT. Clamped by the entitlement server-side, and without it the environment is allowed ten minutes — so a wedged environment costs you ten before you learn anything. Seconds to a couple of minutes suits most commands; raise it for builds. | |
| environment | Yes |
TDQS
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already indicate openWorldHint=true and destructiveHint=true, but the description adds valuable behavioral context: it is not a shell, it returns exit code and output, and a paused environment resumes for it. These details go beyond the annotations and help the agent understand execution semantics.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
The description is two sentences, front-loaded with the core purpose. Each sentence adds essential information without redundancy, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool has 5 parameters with nested objects and no output schema, the description covers the primary behavior (command execution, exit code/output) and key usage notes (argv, shell). It lacks detailed parameter explanations but the schema covers timeout_ms, and the annotations cover safety aspects. This is reasonably complete for a command runner tool.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
With schema description coverage at only 20%, the description should compensate. It adds meaning to the argv parameter (list form, explicit shell usage) and mentions environment behavior, but does not explain cwd, env, or environment beyond that. The timeout_ms parameter already has a schema description. This is adequate but not comprehensive.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description explicitly states 'Run one command in an environment and get its exit code and output,' which clearly identifies the verb, resource, and outcome. It also distinguishes itself from a shell, clarifying its scope and differentiating it from sibling tools that manage environments.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides clear usage instructions: 'pass argv as a list, and ask for a shell explicitly with ["/bin/sh","-lc","…"] if you want one.' It also notes that a paused environment resumes to serve the command, giving practical context. However, it does not explicitly discuss when to use this versus alternatives, though siblings are not direct alternatives.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Tool Schema Changelog
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
7 tool updates
v0.1.0- First observed
checkpoint_environment - First observed
create_environment - First observed
delete_environment - First observed
get_credit_balance - First observed
get_environment - First observed
list_environments - First observed
run_command
TDQS
Scored across 7 tools
Each tool addresses a distinct concern: credit balance, environment lifecycle, and command execution are cleanly separated. Even checkpoint_environment is unambiguous because it explicitly forks an environment into a new one.
All tools follow a consistent verb_noun pattern in snake_case, such as create_environment, list_environments, and delete_environment. Singular/plural usage is natural and predictable.
Seven tools is well-scoped for managing persistent development environments: credit checking, creation, listing, inspection, command execution, forking, and deletion/archival. No tool feels redundant or out of place.
The environment lifecycle is covered end-to-end: create, read (list/get), fork/checkpoint, execute commands, and delete/archive. The credit balance tool fills the one supporting need for running environments, leaving no obvious dead ends.
Maintenance
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Hosted MCP runtime where your agent publishes its own tools by tool call and keeps working.
MCP server for your apps' tools and custom tools, plus hosted AI agents and approval-gated workflows
Your org's AI agents, tasks, runs, search, and brain files as MCP tools and resources.
Hosted MCP server and Agent Skills for specs, engineering threads, and project memory.
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